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Software Engineer, Terminal Interface
Normal Computing · New York City, New York, USA
$200k–400k
6 days ago
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Talent Operations Specialist
Normal Computing · Palo Alto, California, United States
$140k–190k
15 days ago
♡
Thermodynamic Hardware Resident
Normal Computing · New York City, New York, USA
$150k
20 days ago
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Hardware Engineer, Architect
Normal Computing · Palo Alto, California, United States
$105k–250k
23 days ago
♡
Software Engineer, Agent Systems
Normal Computing · New York City, New York, USA
$200k–400k
40 days ago
♡
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Software Engineer, Terminal Interface
Normal Computing · New York City, New York, USA
Pay
$200k–400k
Setting
On-site
NORMAL COMPUTING | BUILD WITH US
Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, Silicon Valley (Mountain View), London, Copenhagen, and Seoul.
THE ROLE
Normal CLI is how semiconductor engineers do AI-assisted verification work. It is a large interactive terminal application, built in Python and Textual, that design verification engineers keep open all day, usually in environments we do not control: remote workstations inside chip companies, SSH sessions, tmux, Windows and WSL. Our users are accustomed to terminal products, and for many of them this is the first and only surface of Normal they will use. We expect that to remain true.
We are hiring the engineer who will own it as a product: productionizing what began as a research tool and giving it a dedicated end-user focus. You will own the interaction model and the information design — how people enter and edit instructions, how a long agent run stays legible while it streams, how tool use and proposed changes are presented for review, and how work is interrupted, resumed, and recovered after a failure. You will also own the local session client beneath it, and be a leading voice in the client API the rest of our product is built on.
The boundaries matter here. Our ML and research engineers keep the harness — the skills, tools, hooks, and model behavior that make the agent good at chip verification. You take the application those capabilities reach users through. You will sit on the product engineering team that also builds our desktop workbench, our web product, and our agent orchestration, so the terminal moves into the same product as everything else, with the same vocabulary, state, and quality bar.
On any given day, you might rework how a long verification run folds and summarizes itself so an engineer can read it at a glance, chase down why text input breaks under one customer's terminal and IME combination, turn a recurring support thread into a reusable component and a snapshot test, or push back on a runtime event shape that cannot be rendered well.
WHAT YOU WILL OWN
- The terminal application: Information architecture and interaction across commands, navigation, input and editing, streamed output, progress, review, interruption, recovery, empty states, and errors that tell the user what to do next.
- Cross-platform behavior: Correct, fast behavior across terminals, shells, multiplexers, remote sessions, macOS, Linux, Windows and WSL, non-English input and IMEs, and constrained customer environments.
- The client boundary: The local session client, and a leading voice in the structured-event interface it consumes. You shape what the runtime emits so the UI does not have to infer intent from formatted text.
- Standards other contributors build against: Define the command, picker, progress, output, and review patterns that research and product engineers use when they add domain workflows, and keep the experience coherent as they do.
- Responsiveness under load: Streaming, cancellation, concurrency, and event-loop behavior for work that runs for a long time and must stay interruptible and understandable throughout.
- A coherent product across surfaces: Shared terminology, state, authentication, and handoffs between the terminal and the rest of our EDA product, so users moving between them do not have to learn two systems.
- Architecture: Evolve a large Textual application toward reusable components and a clear line between product UI, domain logic, and runtime concerns.
- Confidence to change it: Snapshot and visual-regression coverage, packaging, installation, self-update, and the tests that make it safe to change an interactive application people depend on.
WHAT MAKES YOU A GREAT FIT
- 4+ years of software engineering experience, including significant time building and maintaining an interactive terminal application, TUI, or comparably rich local client — not command wrappers.
- Experience taking on an existing codebase and improving it without breaking what already worked.
- Familiarity with what makes terminal software hard: keyboard and text input, rendering performance, inconsistent terminal capabilities, process and signal handling, and behavior that differs across platforms and environments.
- Strong engineering fundamentals. The application is written in Python and Textual; we weigh depth and judgment above prior experience with either.
- Experience with event-driven or asynchronous applications: streaming data, local processes, cancellation, concurrency, persistence, and recovery from partial failure.
- A high bar for interface details — defaults, error messages, empty states, wording — and a habit of fixing them before users report them.
- The ability to debug across boundaries, from a keystroke in a terminal emulator through the application to the runtime.
- Experience testing interactive software, and judgment about which behavior is worth pinning down.
- Comfort working with researchers and domain experts, and the ability to learn an unfamiliar technical domain well enough to represent an expert workflow accurately.
- Pragmatic judgment about when to invest in a durable abstraction and when to ship the straightforward version.
BONUS POINTS
Experience with any of the following is helpful, but not required:
- Textual, Rich, prompt-toolkit, curses, Bubble Tea, Ratatui, Ink, or another terminal UI framework
- PTYs, terminal emulation, multiplexers, or remote shell and host abstractions
- Designing human-in-the-loop experiences for coding agents, AI tools, or other long-running automated systems
- Cross-platform packaging, self-update systems, internationalization, IME support, or visual regression testing
- Electron or another desktop framework, particularly embedding a CLI, TUI, or agent runtime
- Semiconductors, EDA, or hardware engineering workflows
Equal Employment Opportunity Statement
Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.
Accessibility Accommodations
Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com.
Privacy Notice
By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Privacy Policy.
Listed by Normal Computing for a position based in the United States. Employers on this board attest they are hiring domestically.
Talent Operations Specialist
Normal Computing · Palo Alto, California, United States
Pay
$140k–190k
Setting
Hybrid
NORMAL COMPUTING | BUILD WITH US
Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, Silicon Valley (Mountain View), London, Copenhagen, and Seoul.
THE ROLE
As our Talent Operations Specialist, you will own and scale the engine behind how Normal hires world-class talent across hardware, software, and AI. You sit at the strategic center of our global talent organization, acting as the right hand to our Head of Talent to build high-efficiency recruiting workflows, maintain our data integrity, and eliminate friction across five global time zones.
At Normal, we operate in a fast-moving, highly evolving environment where priorities shift and ambiguity is constant. You are someone who thrives on context-switching—effortlessly pivoting between long-term system architecture and immediate operational priorities. Rather than just manually moving candidates through calendars, you take complete ownership of our talent infrastructure: optimizing Ashby, building real-time executive dashboards, automating scheduling flows, and ensuring our recruiting operation runs on rails as we scale.
WHAT YOU’LL OWN
- Recruiting Systems & Ashby ATS Architecture: Serve as the primary admin for Ashby. Permission and seat management, pipeline stages, build custom candidate communication templates, configure auto-scheduling rules, and manage integrations across our tech stack (Slack, Notion, AI Notetaker, Google Workspace).
- Candidate Data Integrity and Compliance Operations: Own the day-to-day health of candidate data in Ashby. Maintain retention and consent configurations, execute scheduled record dispositions, monitor duplicate and fraud-flagged records, and keep candidate data practices aligned with Normal’s published privacy commitments across US and global applicants.
- Talent Analytics & Reporting: Build and maintain recruiting dashboards to track funnel conversion, candidate velocity, source effectiveness, and interviewer loads. Deliver data-backed insights to the Head of Talent and leadership to optimize hiring SLAs.
- Process Automation & AI Workflow Optimization: Evaluate, scope, and govern AI tools, automated scheduling logic, and low-code integrations to reduce admin overhead, improve response times, and elevate candidate experience.
- Interviewer & Hiring Manager Enablement: Partner with recruiting leads to standardize interview loops, establish scorecard guidelines, onboard new interviewers, and build clear Notion documentation for team-wide hiring practices.
- Global Logistics & Vendor Operations: Oversee candidate touchpoints and job board posting distribution across US, European, and APAC markets.
- Special Projects & Strategic Support: Partner directly with the Head of Talent on high-impact initiatives, including headcount planning support, talent brand launches, recruiting event logistics, and strategic ad-hoc projects.
- Interview Coordination (Backup and Surge): Provide secondary coverage for interview scheduling when volume spikes or primary coordination is unavailable. Roughly 15-20% of the role.
WHAT MAKES YOU A GREAT FIT
- Talent Ops or Advanced Coordination: You have experience in a fast-scaling tech startup, high-growth environment, or deep-tech company.
- Extreme Ownership & Accountability: You treat the recruiting engine as your own product. You flag problems while they are small, fix broken processes without being asked, and close loops relentlessly.
- Comfort with Context-Switching & Ambiguity: Highly adaptable and composed when priorities shift in a fast-paced, evolving startup environment.
- Mastery of ATS Infrastructure: Hands-on experience administering Ashby (or Greenhouse/Lever) with a track record of setting up structured pipelines, custom fields, offer workflows, and automated scheduling rules.
- Data-Fluent & Analytical: Comfortable working with recruiting metrics, building custom reports, identifying pipeline bottlenecks, and presenting data clearly to stakeholders.
- Systems & Automation Mindset: Passionate about documentation, process hygiene, and using modern tools (Slack, Notion, AI assistants, low-code automations) to replace manual administrative work.
- Global & Cross-Functional Comfort: Experienced in navigating multi-time-zone communication (US, Europe, APAC) with high attention to detail and proactive communication default.
BONUS POINTS
- Advanced experience specifically with Ashby
- Experience supporting fast-moving technology startups.
- Background in setting up interviewer calibration modules or candidate NPS loops
Equal Employment Opportunity Statement
Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.
Accessibility Accommodations
Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com.
Privacy Notice
By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Privacy Policy.
Listed by Normal Computing for a position based in the United States. Employers on this board attest they are hiring domestically.
Thermodynamic Hardware Resident
Normal Computing · New York City, New York, USA
Pay
$150k
Setting
On-site
Co-design of algorithms and benchmarking of applications for Normal's thermodynamic computing hardware
Listed by Normal Computing for a position based in the United States. Employers on this board attest they are hiring domestically.
Hardware Engineer, Architect
Normal Computing · Palo Alto, California, United States
Pay
$105k–250k
Setting
Hybrid
NORMAL COMPUTING | BUILD WITH US
Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, San Francisco, London, Copenhagen, and Pangyo.
THE ROLE
As a Hardware Engineer, Architect, you will define the silicon and system microarchitecture for our custom unconventional compute platform—driving the architectural trade-offs that unlock a 100–1000x leap in energy efficiency over traditional digital chips for LLM and diffusion model inference.
You will lead the hardware/software co-design efforts to break the von Neumann memory wall. By translating transformer architectures (KV-cache management, attention mechanisms) and diffusion execution flows into custom mixed-signal compute tiles, memory hierarchies, and tile interconnects, you will set the blueprint for our hardware. Working closely with compiler, RTL, and analog teams, you will build performance models, establish microarchitectural specifications, and ensure our custom silicon delivers maximum throughput-per-watt on real-world generative AI workloads.
WHAT YOU WILL OWN
- Compute Architecture: Help define the architecture and microarchitecture of novel AI accelerator compute blocks: PE array design, datapath organization, and support for efficiency techniques such as sparsity exploitation and reduced-precision computation. The compute tile is the surface where Normal's research advantages have to show up in silicon, and you are one of the people responsible for making sure they do.
- Workload-to-Hardware Translation: Translate workload analysis and research findings into hardware specifications. Identify where architectural innovation creates the most leverage, define the structures that realize it, and produce microarchitecture documents unambiguous enough for RTL engineers to implement against. You work closely with them through implementation, not over the wall from it.
- Full-Stack PPA Tradeoffs: Reason across the full stack and defend PPA tradeoffs at every level. Move between algorithm-level workload behavior, memory hierarchy, on-chip interconnect, and physical design constraints. Make the call when the data is incomplete, and articulate why under scrutiny from our Systems Architect and the research team.
- ISA Co-Design: Partner with the compiler lead on ISA co-design. The programming model and the microarchitecture are defined together, and you are accountable for both sides meeting in the middle.
- Prototyping Strategy: Direct block-level pre-silicon validation. Decide which microarchitecture questions need to be answered, and the appropriate platform. Partner with our FPGA Design Engineers, who own implementation and bring-up, to de-risk decisions before tapeout. Work with the Systems Architect to make sure there are no gaps from block to System-level validation.
- Research Fluency: Stay current with the AI accelerator research landscape and be able to articulate clearly where Normal's approach differs from existing solutions and why that matters. This is a research-adjacent seat and you are expected to read, possibly publish, and not just consume.
WHAT MAKES YOU A GREAT FIT
- A degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent work experience. PhD welcome but not required; the bar is the work, not the credential.
- Substantial experience in architecture or microarchitecture of high-performance digital systems: AI accelerators, compute engines, or similarly complex logic. You have shaped and directed the structures inside a chip, not just consumed them from the outside.
- Fluency moving between algorithm-level analysis and hardware specification. You can read a profile of a workload and translate it into datapath widths, pipeline stages, and area/power estimates without losing the thread on either side.
- Experience with simulation-driven architecture. You have used cycle-accurate or analytical models to make and defend design decisions before RTL exists, and you know which questions each tool can answer and which it cannot.
- Familiarity with quantization and reduced-precision approaches for inference and their implementation implications. You understand the cost of a bit at the hardware level, not just the model level.
- Experience writing microarchitecture specifications and working closely with RTL engineers through implementation.
- Proficiency in Python or C++ for performance modeling and analysis, and familiarity with SystemVerilog or equivalent RTL.
- Comfort operating in an environment where the architecture is actively being discovered alongside the work. You do not need the answer to be already known to make progress on it.
Equal Employment Opportunity Statement
Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.
Accessibility Accommodations
Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com.
Privacy Notice
By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Privacy Policy.
Listed by Normal Computing for a position based in the United States. Employers on this board attest they are hiring domestically.
Staff Accountant
Normal Computing · Palo Alto, California, United States
Pay
$158k–228k
Setting
Hybrid
NORMAL COMPUTING | BUILD WITH US
Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, Silicon Valley (Mountain View), London, Copenhagen, and Seoul.
THE ROLE
We are hiring a Staff Accountant to build the core of Normal's accounting function as the company scales across two product lines and five offices. You will partner with our Head of Finance to establish the close process, the systems, and the internal controls that Normal's growth depends on, from revenue recognition through diligence readiness. Much of this infrastructure is being defined now, which means the work you do shapes how finance operates at Normal for years, and you will build it with AI as a first-class part of the workflow rather than an afterthought.
WHAT YOU WILL OWN
- Own the financial close. Run the monthly, quarterly, and annual close, including accruals, journal entries, account reconciliations, and standard reporting, and work closely with FP&A to deliver reporting of historical financial data.
- Implement and maintain accounting systems. Build the systems that support revenue recognition, KPI reporting, and accrual and reconciliation workflows, documenting accounting conclusions and policy positions as the function's precedent.
- Manage financial operations. Own tax compliance, external due diligence requests, and AR and AP functions end to end.
- Drive process and controls. Lead process improvements, systems improvements, and internal controls that support the company's growth at scale.
- Build an AI-native accounting capability. Stand up an accounting function from the ground up that uses AI to move faster and cover more ground, while keeping verification and judgment in your own hands.
WHAT MAKES YOU A GREAT FIT
- 5+ years of accounting experience, including experience building an accounting function at a high-growth startup.
- Public accounting experience, with a Big 4 background a plus.
- A BA or BS in accounting or a related field, or equivalent experience.
- Low ego and high agency: you solve problems wherever you find them, whatever your role or level.
Equal Employment Opportunity Statement
Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.
Accessibility Accommodations
Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com.
Privacy Notice
By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Privacy Policy.
Listed by Normal Computing for a position based in the United States. Employers on this board attest they are hiring domestically.
Software Engineer, Agent Systems
Normal Computing · New York City, New York, USA
Pay
$200k–400k
Setting
Hybrid
NORMAL COMPUTING | BUILD WITH US
Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, Silicon Valley (Mountain View), London, Copenhagen, and Seoul.
THE ROLE
As a Software Engineer at Normal, you will build the backend runtimes and distributed systems behind our AI products. You'll design orchestration services, execution environments, internal APIs, persistence layers, and observability systems that allow AI agents to perform long-running work reliably.
These systems coordinate workloads across distributed environments, execute code and tools securely, preserve state across long-running sessions, and recover cleanly from failures. Your work will turn ambitious AI prototypes into dependable products used in real customer workflows.
The role spans backend, AI, and platform engineering. Its focus is the application and runtime layer but not general-purpose cloud infrastructure or company-wide developer operations. You'll work closely with product, AI, research, and platform engineers to define the interfaces between AI capabilities, execution environments, and production services.
On any given day, you might design the execution model for a new AI capability, build an orchestration service for autonomous workflows, improve the scheduling and isolation of distributed workloads, or create an API that makes a complex runtime capability easy for other engineers to use.
WHAT YOU WILL OWN
- Runtime and Orchestration: Build the services that manage agent execution, session lifecycles, long-running workflows, and distributed workloads.
- Backend Systems and APIs: Design reliable services, data models, and internal APIs used by product engineers, AI engineers, and execution systems.
- State and Failure Handling: Develop clear models for persistence, retries, queues, leases, cancellation, recovery, and other distributed-systems concerns.
- Execution Environments: Build software that schedules and manages containerized workloads in Kubernetes-backed environments, including lifecycle, isolation, autoscaling, and resource management.
- Reliability and Observability: Make evolving systems easier to operate through thoughtful metrics, tracing, debugging tools, and well-defined failure modes.
- Developer Experience: Create abstractions and tools that allow other engineers to extend the platform without needing to understand every underlying implementation detail.
- Prototype-to-Production Engineering: Turn promising prototypes into durable systems by clarifying boundaries, hardening critical paths, and introducing operational patterns that scale.
- Technical Design: Facilitate design discussions around runtime architecture, API boundaries, state management, execution models, and operational tradeoffs.
WHAT MAKES YOU A GREAT FIT
- 4+ years of software engineering experience in backend systems, distributed systems, developer platforms, production infrastructure, or a related area.
- Strong backend engineering fundamentals, including API design, data modeling, concurrency, debugging, and testing.
- Experience designing and operating production services where reliability, observability, and maintainability matter.
- Experience reasoning about distributed state and failure modes, including retries, queues, leases, scheduling, idempotency, and long-running workflows.
- Practical experience with containers and Kubernetes-backed systems, including workload lifecycle, networking, resource limits, and production debugging.
- Experience with production data systems such as Postgres, Redis or Valkey, and object storage.
- Experience building orchestration systems, workflow engines, job schedulers, sandboxes, developer platforms, or distributed execution systems.
- A track record of designing APIs and abstractions that other engineers can use confidently.
- Pragmatic judgment in fast-moving environments: you know when to improve an abstraction, simplify it, or ship the straightforward version.
- A strong sense of ownership for how your software behaves in production and how effectively others can use it.
BONUS POINTS
- Experience building systems for AI agents, model orchestration, code execution, or other LLM-powered products.
- Deep Kubernetes knowledge, such as controllers, scheduling, networking, storage, autoscaling, or resource isolation.
- Experience with secure or sandboxed code execution.
- Background in reliability engineering, infrastructure software, or developer platforms at meaningful scale.
- Experience working in high-growth environments where systems and ownership boundaries are still taking shape.
Equal Employment Opportunity Statement
Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.
Accessibility Accommodations
Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com.
Privacy Notice
By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Privacy Policy.
Listed by Normal Computing for a position based in the United States. Employers on this board attest they are hiring domestically.
Hardware Engineer, PCB
Normal Computing · New York City, New York, USA
Pay
$200k–400k
Setting
Hybrid
NORMAL COMPUTING | BUILD WITH US
Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, Silicon Valley (Mountain View), London, Copenhagen, and Seoul.
THE ROLE
Normal Computing is redefining computing for the next 20 years by optimizing LLM and Diffusion inference by 100–1000x through combining thermodynamic computing and CIM technology. You will own the end-to-end development of our CIM substrate from architecture and schematic design to layout, tapeout, custom PCB development, and post-silicon bring-up.
WHAT YOU WILL OWN
- End-to-end PCB design flow: lead the full PCB development cycle including research, design, and evaluation of custom chips
- Silicon bring-up: lead post-silicon correlation and validation efforts including root-cause analysis and general debug
- PCB bring-up: ensure the PCB you designed and manufactured is fully functional as intended
- Cross-functional collaboration: work alongside analog, digital, and ML engineers to further improve system-level PPA.
WHAT MAKES YOU A GREAT FIT
- Owned multiple PCBs end-to-end through design, simulation, fabrication and bringup
- Familiar with common PCB tools, including Altium, Allegro, OrCAD, Xpedition
- Built PCBs for expansion formats like PCIe, and including components like FPGAs, high-speed memories, flash memories, and various connectors like 100G ethernet
BONUS POINTS
- Lead, fabricated, brought up custom PCBs to evaluate custom CIM chips
- Experienced and comfortable in a lab bench environment including soldering with a microscope
- Have used scripting languages (i.e. Python, Perl) to automate design flows and data post-processing
Equal Employment Opportunity Statement
Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.
Accessibility Accommodations
Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com.
Privacy Notice
By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Privacy Policy.
Listed by Normal Computing for a position based in the United States. Employers on this board attest they are hiring domestically.
Research Engineer, Algorithms
Normal Computing · New York City, New York, USA
Pay
$200k–400k
Setting
Hybrid
NORMAL COMPUTING | BUILD WITH US
Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, San Francisco, London, Copenhagen, and Pangyo.
THE ROLE
You will develop the computational methods that make AI inference run efficiently on Normal's thermodynamic hardware. The core challenge is not adapting standard GPU kernels to a new chip. It is rethinking how operations like attention, memory access, and long-context decoding behave when the underlying substrate uses stochastic analog computation in memory rather than conventional digital logic.
Normal's ASICs run the heaviest operations of large model inference inside memory itself. Your job is to develop the algorithms that exploit this natively: understand what transformer and diffusion workloads are well-suited to stochastic analog execution, design numerical methods that map onto the hardware's physical dynamics, and validate them against real silicon or high-fidelity simulation.
This is a co-design role. The hardware and the algorithms are developed in parallel, which means you will influence architectural decisions, not just implement against a fixed specification. The strongest candidates have a deep understanding of both large model inference and the mathematics of stochastic systems, and have built systems that run on real hardware, not just in theory.
WHAT YOU WILL OWN
- Algorithm Development: Develop algorithms for transformer inference workloads running on stochastic analog processing-with-memory hardware.
- Software/Hardware Co-Design: Work directly with hardware and architecture teams to shape what the chip can and should compute natively.
- Numerical Methods: Design numerical methods that exploit thermal noise and analog dynamics rather than working around them.
- Evaluation & Benchmarks: Build evaluation frameworks and benchmarks that characterize algorithm behavior on real hardware or simulation.
- Workload Translation: Translate insights about model workloads into constraints and opportunities for hardware design.
- Rapid Prototyping: Prototype and iterate rapidly as hardware evolves from simulation to silicon.
- Optimizing Performance: at the gate level and the algorithmic level. and algorithms (expand/review), reinforcement learning tools.
WHAT MAKES YOU A GREAT FIT
- Deep understanding of large model inference: attention mechanisms, KV cache, long-context decoding, memory bandwidth constraints
- Experience with inference optimization: quantization, sparsity, kernel fusion, or memory-efficient attention
- Familiarity with stochastic systems, probabilistic methods, numerical analysis, or analog computation
- Experience implementing algorithms close to hardware, not just in high-level frameworks
- Comfort reasoning from first principles about what a novel substrate can do efficiently
- Track record of taking ideas from theory to working implementation on real hardware
- Strong programming skills in Python and at least one systems language
- Collaborative instinct and ability to work across hardware, architecture, and software teams
BONUS POINTS
- PhD in machine learning, applied mathematics, physics, electrical engineering, or a related field
- Exposure to analog or mixed-signal systems, in-memory compute, or non-von-Neumann architectures
- Experience working on hardware that did not yet exist when you joined
- Publications or open-source work in efficient inference, stochastic algorithms, or novel computing
Equal Employment Opportunity Statement
Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.
Accessibility Accommodations
Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com.
Privacy Notice
By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Privacy Policy.
Listed by Normal Computing for a position based in the United States. Employers on this board attest they are hiring domestically.
Content Strategist
Normal Computing · New York City, New York, USA
Pay
$140k–236k
Setting
Hybrid
NORMAL COMPUTING | BUILD WITH US
Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, Silicon Valley (Mountain View), London, Copenhagen, and Seoul.
YOUR ROLE
We are hiring a Content Strategist to partner on how Normal communicates its products and mission. Communications at Normal is core to the business: telling the story well is how we attract the best people, reach the customers and partners who grow the company, and express the mission to the world. You will embed with our product, engineering, and research teams, a standing participant in their product and roadmap discussions, and turn frontier work into content that ships.
Few communications roles offer this depth and breadth. Solving the AI energy crisis is a challenging and multifaceted story to tell, and most of its defining pieces have not been written yet. You will write them. Normal is naming computing categories that have not existed before, and until the words exist, the category doesn't. The work is demanding, and that is also the draw: you will learn physics, silicon, and AI from the people inventing them, and grow faster for it.
Sometimes you will draft from a blank page, and sometimes you will polish, finish, or partner with contributors to bring a piece to publication. In every case you own the outcome: taking content to near-complete, gathering final input from the right reviewers, and shipping it, every piece connected to our canonical language and approved claims. Whoever started the piece, it comes out sharper for having passed through your hands.
You will work closely with the Head of Communications on editorial strategy and priorities, while owning the drafting, production, and publishing volume that keeps the cadence of content steady. The partnership comes with context on the business, the brand, and the audiences we serve, and context and feedback that compound into the work.
The core of the role is creativity and critical thinking: holding the pen on original content, bringing a clear strategy to every piece you ship, and drawing the same originality out of the engineers and leaders you partner with. Being generative alongside AI is now part of the craft: the tools accelerate the work and keep it consistent, while judgment, taste, and access to what only this team knows stay scarce, and those are what you add. The work runs on internalized understanding. Ask questions until you understand how something actually works, then write from that understanding in Normal's voice, and the experts should recognize their work in the final piece without needing to rewrite it.
On any given day, you might draft a blog post on thermodynamic computing with our Chief Scientist, build a conference talk alongside the speaker who will deliver it, run the workback for a conference submission, refresh a product page against our canonical language, or ship the social post that announces a new hire.
WHAT YOU WILL OWN
- Draft and ship external content. Produce website copy, thought leadership blog posts, product content, social posts, video scripts, and careers and recruiting copy that carry Normal's mission and products to audiences ranging from verification engineers to semiconductor executives, investors, and policymakers.
- Develop technical narratives. Produce whitepapers, product briefs, proposal content, and technical explainers in collaboration with engineers and researchers, translating work in thermodynamic computing and AI-accelerated silicon engineering into precise narratives. Generalities and hype don't survive contact with these readers. For deeply technical content, the experts own the substance; you shepherd it, shaping the narrative and running the program that gets it shipped.
- Own brand and message consistency. Ensure the claims we publish are accurate, substantiated, and consistent with approved company language across every surface where the company speaks, and maintain the canonical language sources as our positioning evolves.
- Support external engagements. Partner with speakers to build their talks, preparing keynote narratives, slide decks, talking points, and briefing documents for conferences, executive briefings, and partner meetings, and execute on event days: briefing the speaker on site, coordinating in real time with the team, and shipping same-day social coverage.
- Drive editorial work to publication. Build workback plans from hard external deadlines, sequence and book reviewers in advance, keep stakeholders updated as work moves, and escalate early when it doesn't. Coordinate content across Product, Engineering, and GTM, and manage external partners including designers and production vendors.
- Elevate internal communications. Partner with company leaders on content for all-hands and companywide moments, and produce internal communications that keep a global team informed and aligned.
- Editorial partnership. Work with engineers, researchers, and leaders on the content they originate, strengthening the argument and bringing consistency of voice and a unified quality bar to everything Normal publishes, and advise our thought leaders on where and how to share their most important messages, drafting in their voices when the moment calls for it.
- Contribute to content strategy. Surface content opportunities, propose new formats and series, and bring pattern recognition from your work with engineers, audiences, and events into the team's editorial planning.
WHAT MAKES YOU A GREAT FIT
- 5+ years in communications, content strategy, technical writing, science journalism, or a related field, or equivalent experience. Journalists from scientific publications and PhDs who write clearly about their field are strong candidates here.
- Exceptional original writing and editing, with a portfolio of shipped work you drafted and can speak to in depth.
- Technical acumen and curiosity: you learn new domains quickly, earn credibility with the engineers you work with, understand the mechanism before you write the sentence about it, and contribute thinking while you ramp.
- A track record of driving multi-stakeholder deliverables to publication against hard external deadlines, with the instincts to run workbacks, sequence busy reviewers, and escalate early.
- Comfort engaging on design: you think about communications artifacts holistically, from the argument to the visual presentation, and partner closely with brand design.
- Meticulous attention to detail and strong judgment with confidential information.
- Low ego and high agency: you solve problems wherever you find them, whatever your role or level.
- Willingness to travel up to 25% for team meetings, industry conferences, and customer engagements.
Equal Employment Opportunity Statement
Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.
Accessibility Accommodations
Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com.
Privacy Notice
By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Privacy Policy.
Listed by Normal Computing for a position based in the United States. Employers on this board attest they are hiring domestically.
Silicon Software Lead
Normal Computing · New York City, New York, USA
Pay
$200k–400k
Setting
Hybrid
NORMAL COMPUTING | BUILD WITH US
Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, San Francisco, London, Copenhagen, and Pangyo.
THE ROLE
Normal's ASIC computes using stochastic analog dynamics in memory, and the software layer that makes it programmable and performant for real inference workloads does not yet exist in any standard form. As our Silicon Software Lead, you will lead the team that creates it: the compiler, runtime, kernels, drivers, and hardware abstraction layer that turn our chip into a platform. You will set technical direction, stay hands-on in the stack, and co-design with hardware architects so that software constraints shape the silicon rather than arriving after it.
This is a role for someone who has built software for hardware that did not exist yet, and wants to do it where the software genuinely impacts and optimizes the hardware.
WHAT YOU WILL OWN
- Team Leadership: Lead and grow the silicon software team spanning compiler, runtime, and systems software, staying close enough to the code to review designs and unblock hard problems directly.
- Software Stack Architecture: Own the architecture of the stack from ML framework ingestion through compilation, scheduling, and memory management to execution on Normal hardware.
- Software/Hardware Co-Design: Partner with silicon architects on ISA definition and the hardware abstraction layer, ensuring the chip is compilable and programmable, not just simulatable.
- Runtime and Tooling: Drive development of the runtime, kernels, drivers, profiling, and debugging tools that make the hardware usable for real inference workloads.
- Simulation-to-Silicon Continuity: Keep the software stack running against simulation, FPGA prototypes, and silicon as the hardware matures, so software development never waits on tapeout.
- Roadmap and Hiring: Set the silicon software roadmap, define milestones against the hardware program, and hire the engineers who deliver it.
WHAT MAKES YOU A GREAT FIT
- Substantial experience building software stacks for accelerators or non-standard hardware targets: compilers, runtimes, kernels, or drivers
- Experience leading engineers as a technical lead or manager while staying hands-on in design and code
- Strong systems programming skills in C++, Rust, or equivalent, with fluency in Python
- Deep understanding of ML inference workloads and the constraints that shape their execution on hardware
- Experience with compiler frameworks such as MLIR or LLVM, or with inference runtimes and kernel development
- Comfort building software for hardware that is still evolving, from simulation through bring-up
- Track record of hiring and developing strong systems engineers
BONUS POINTS
- Experience taking an accelerator software stack from zero to production at a startup or new hardware program
- Experience with in-memory compute, processing-in-memory, or analog hardware interfaces
- Contributions to open-source compiler or runtime infrastructure
- Experience with hardware-software co-design where software insights shaped ISA or architecture decisions
Equal Employment Opportunity Statement
Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.
Accessibility Accommodations
Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com.
Privacy Notice
By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Privacy Policy.
Listed by Normal Computing for a position based in the United States. Employers on this board attest they are hiring domestically.
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