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ABOUT THE COMPANY Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy. At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling (BeyondWeb https://www.datologyai.com/blog/beyondweb) and pretraining with domain-specific data (The Finetuner’s Fallacy https://www.datologyai.com/blog/finetuners-fallacy). We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models. Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data. This role is based in Redwood City, CA. We are in office 4 days a week. ABOUT THE ROLE You'll shape the way users experience our platform from the ground up. Our users are ML engineers and researchers, and the workflows they run are long, expensive, and technically dense. Your job is to make those systems legible: designing the configuration surfaces, telemetry, and visualizations that let an engineer parameterize a curation pipeline, inspect its behavior at runtime, and evaluate the quality of the dataset it produces. This role asks for high visual craft, and the ability to take a genuinely complex feature and define a design for it that feels obvious. You'll own the visual quality of what lands in production and partner closely with engineers to get it there. You'll work with leadership, engineering, research, and customers, with a rare opportunity to influence product direction at an early stage. WHAT YOU'LL WORK ON - Create and design key user-facing features and components of our data curation platform end to end, from concept to production - Define the design principles for an enterprise platform, and set the bar for clarity and confidence in workflows where the stakes are high - Establish and evolve an intuitive, scalable design system, style guide, and illustration language so the product scales consistently - Deliver high quality assets—icons, illustrations, and motion—that hold up across the product - Create wireframes, prototypes, and high-fidelity designs that balance user needs with real technical constraints - Conduct user research, usability testing, and analysis to understand pain points and validate design solutions - Collaborate with engineering and research teams to define both long-term strategy and short-term deliverables - Help establish our design culture as an early design team member THE AREAS YOU'LL DESIGN ACROSS: - Technical workflows. Front-end UI for setting up, launching, monitoring, and intervening in long-running curation and training jobs - Data visualization. Making dataset composition, quality, and cost legible at a glance - Onboarding and integration. Flows that get customers' data into the platform ABOUT YOU - 5+ years of experience designing digital products, with a portfolio showcasing strong UX, UI, and interaction design skills - High visual craft, with the ability to produce finished assets yourself—iconography, illustration, and interface detail that ship - A track record of motion design that is beautiful and intuitive, clarifying what's happening rather than decorating it - You've created intuitive, scalable design systems and style guides from scratch, and evolved them as a product grew - Experience simplifying complex technical concepts into intuitive user experiences - Experience designing data-dense interfaces and data visualization - Experience designing with cross-functional partners for multiple use cases and distinct user types—enterprise technical users alongside ML researchers and scientists - Excellent communication skills with the ability to articulate design decisions to technical and non-technical stakeholders - Proficiency with Figma and other prototyping software - Comfortable working in an ambiguous, fast-paced startup environment - Ability to balance short-term deliverables with long-term vision - Self-motivated problem solver who can work independently while collaborating effectively with cross-functional teams NICE TO HAVE: - You implement your own work—comfortable in HTML and CSS, and shipping front-end code alongside engineers - Experience working with AI tools to prototype and implement designs - Experience designing platform workflows for ML engineers and researchers - Experience designing for technical or enterprise users - Experience working as an early designer at a startup COMPENSATION At DatologyAI, we are dedicated to rewarding talent with competitive salary and meaningful equity. The salary for this position ranges from $180,000 to $250,000. - Starting pay is based on job-related skills, experience, qualifications, and interview performance. Benefits: - 100% covered health benefits (medical, vision, and dental). - 401(k) plan with a generous 4% company match. - Unlimited PTO policy - Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility. - Annual $2,000 wellness stipend. - Annual $1,000 learning and development stipend. - Daily lunches and snacks are provided in our office! - Relocation assistance for employees moving to the Bay Area.

Listed by DatologyAI for a position based in the United States. Employers on this board attest they are hiring domestically.

Engineering

35 days ago

AI Developer Experience & Media Lead

DatologyAI · Redwood City, California, USA

Pay

$160k–230k

Setting

On-site

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ABOUT THE COMPANY Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy. At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling (BeyondWeb https://www.datologyai.com/blog/beyondweb) and pretraining with domain-specific data (The Finetuner’s Fallacy https://www.datologyai.com/blog/finetuners-fallacy). We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models. Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data. This role is based in Redwood City, CA. We are in office 4 days a week. ABOUT THE ROLE In this role, you'll be our expert on social, the person who knows how to make DatologyAI's research travel on X and across the AI community. You'll turn our research into narratives, demos, threads, videos, and launches, build a voice on X that people recognize and trust, and take part in the conversation as it happens. You'll also help our founders and researchers communicate in their own voices. The work sits where engineering meets media. You can read one of our results, understand why it matters, and build a demo or write a thread that a technical audience respects. You have a creator's instincts for hooks, video, distribution, and taste. And you're genuinely active in the AI community on X, replying, experimenting, and engaging, not just posting announcements. You'll build the playbook as you operate it. We have real research worth talking about, credible founders, and an audience that's already here, and we're looking for someone who can meet them where they are and be trusted to run with it. WHAT YOU'LL WORK ON - Technical storytelling and demos. Take our research and product work and turn it into narratives, threads, videos, live demos, and launches that a technical audience finds genuinely interesting. - Company voice on X. Build a recognizable, native voice for DatologyAI on X and run it day to day. Reply, quote-post, and participate in live conversations in real time. - Founder and researcher enablement. Help leadership and our research team show up in their own voices. - Research launches, end to end. Own the public launch of our research across X, the technical blog, and video: the angle, the assets, the sequencing, and the follow-through, so each result gets the attention it deserves. - Community and relationships. Build real relationships with researchers, open-source developers, AI creators, and technical founders. - Feedback loop into product and research. Bring what you learn in the community back to the team, so what we hear from developers and researchers informs what we build and what we say next. - Experiments and measurement. Run experiments across X, technical writing, video, launches, and events. Track what earns attention and trust from the right people, and use it to sharpen what we do next. ABOUT YOU - Technical legitimacy. You can build and explain real AI systems. You can read a paper or a launch brief, understand it, comment on it accurately, and produce a demo or a technically serious thread from it. - X-native. You genuinely live on the platform. You post and reply frequently, participate in live conversations, and have a native tone. We care far more about your reply and quote-post behavior and your taste than your follower count. - Creator instincts. You understand hooks, compression, video, personality, and distribution. You have a recognizable voice and a feel for what makes people stop scrolling and engage. - Ambient participant, not a broadcaster. You interact, experiment, and joke in the conversation rather than only publishing polished company announcements. - Able to write in other voices. You can help a founder or researcher sound like themselves, credibly, without flattening what makes them distinctive. - Self-starter with a bias toward action. You take an objective, build the approach, and run with it. - Startup-ready. Comfortable building the playbook as you operate it, moving fast, and owning outcomes end to end. Nice to Have - Your own audience on X, or a track record of building one, with side projects or demos that have circulated organically - Experience at an AI model or infrastructure company, or in developer relations, developer marketing, or growth engineering - A body of technical content spanning agents, inference, multimodality, coding workflows, or similar - Comfort in front of a camera and the ability to produce short technical video Don't meet every single requirement? We still encourage you to apply. If you're excited about our mission and eager to learn, we want to hear from you! COMPENSATION At DatologyAI, we are dedicated to rewarding talent with a highly competitive salary and significant equity. The base salary range for this position is 160,000 - $230,000. - The candidate's starting pay will be determined based on job-related skills, experience, qualifications, and interview performance. Benefits: - 100% covered health benefits (medical, vision, and dental). - 401(k) plan with a generous 4% company match. - Unlimited PTO policy - Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility. - Annual $2,000 wellness stipend. - Annual $1,000 learning and development stipend. - Daily lunches and snacks are provided in our office! - Relocation assistance for employees moving to the Bay Area.

Listed by DatologyAI for a position based in the United States. Employers on this board attest they are hiring domestically.

Marketing

35 days ago

Field Marketing Manager

DatologyAI · Redwood City, California, USA

Pay

$170k–230k

Setting

On-site

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ABOUT THE COMPANY Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy. At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling (BeyondWeb https://www.datologyai.com/blog/beyondweb) and pretraining with domain-specific data (The Finetuner’s Fallacy https://www.datologyai.com/blog/finetuners-fallacy). We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models. Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data. This role is based in Redwood City, CA. We are in office 4 days a week. ABOUT THE ROLE We're hiring a Field Marketing Manager to own every event we run! Conferences, leadership's speaking engagements, executive dinners, dinners and events with our investors, webinars, and whatever comes next. This is a huge ownership role. You'll take an event from a line on the calendar to a flawless day-of experience: sourcing the venue, wrangling vendors, managing the budget, building the run of show, handling registration and logistics, and running the follow-up. We have a lot in flight, the playbook is being written, and we need someone who can bring order to it and be trusted to run with it! WHAT YOU'LL WORK ON - Conferences and field events. Own our presence end to end: booth, venue, swag, signage, vendors, shipping, staffing, lead capture, and post-event recaps. You handle the logistics so the team can focus on the people they're there to meet. - Leadership's speaking engagements. Source and secure the right speaking opportunities, manage submissions and confirmations, coordinate travel and prep, and run point on-site. - Executive dinners. Plan and run our executive dinners. Find and book the venue, build the guest list with sales and the founders, handle every logistic, execute the night, and drive the follow-up afterward. - Investor dinners and events. Partner with our investors to plan and run co-hosted dinners and events, coordinating across their teams and ours so these come together smoothly and reflect well on everyone involved. - Webinars. Own webinars end to end: platform and setup, run of show, speaker prep, registration, promotion in coordination with the content and social team, live production, and follow-up. - Vendors and budget. Source, negotiate with, and manage vendors, and own event budgets. - Cross-functional coordination. Keep sales, the founders, and leadership aligned on what's happening, when, and what's needed from them, with clear timelines and a single source of truth everyone can rely on. - Measurement and reporting. Track attendance, engagement, pipeline, and ROI across events, and report on what's working so we invest in the events that actually move the business. ABOUT YOU - 3–6 years of field marketing, event marketing, or event production experience, ideally at a B2B technical company such as developer tools, AI infrastructure, data infrastructure, or similar - A proven track record owning events end to end, from sourcing and logistics through day-of execution and follow-up, without needing to be managed through it - Early-stage startup experience; you know what it's like to build the playbook as you execute it - Exceptional project management and organization; you run multiple events in parallel with overlapping timelines and never drop a ball - Detail-oriented in a way that's load-bearing for everyone around you, because the details are what make an event feel effortless - Comfortable interacting directly with founders, executives, investors, and senior guests, with the polish and judgment those rooms require - Strong vendor management and negotiation skills, and comfort owning a budget - Willing to travel for events Nice to have - Experience running executive or investor dinners and other high-touch, small-format events - A network of venues, vendors, and event partners in the Bay Area and at major industry conferences - Familiarity with webinar and event platforms, registration tooling, and lead capture - Experience running events at a startup or as part of a small, fast-moving marketing team Don't meet every single requirement? We still encourage you to apply. If you're excited about our mission and eager to learn, we want to hear from you! COMPENSATION At DatologyAI, we are dedicated to rewarding talent with highly competitive salary and significant equity. The base salary range for this position is $170,000 to $230,000 - The candidate's starting pay will be determined based on job-related skills, experience, qualifications, and interview performance. Benefits: - 100% covered health benefits (medical, vision, and dental). - 401(k) plan with a generous 4% company match. - Unlimited PTO policy - Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility. - Annual $2,000 wellness stipend. - Annual $1,000 learning and development stipend. - Daily lunches and snacks are provided in our office! - Relocation assistance for employees moving to the Bay Area.

Listed by DatologyAI for a position based in the United States. Employers on this board attest they are hiring domestically.

Product Management

148 days ago

Product Manager

DatologyAI · Redwood City, California, USA

Pay

$215k–300k

Setting

On-site

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ABOUT THE COMPANY Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy. At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling (BeyondWeb https://www.datologyai.com/blog/beyondweb) and pretraining with domain-specific data (The Finetuner’s Fallacy https://www.datologyai.com/blog/finetuners-fallacy). We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models. Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data. This role is based in Redwood City, CA. We are in office 4 days a week. ABOUT THE ROLE As our first Product Manager, you will own the product strategy and roadmap for our enterprise data curation platform. This is a high-leverage, high-ownership role where you’ll build the function from the ground up. You'll work at the intersection of cutting-edge ML research and enterprise software, translating deep technical capabilities like automated data selection, deduplication, batching, multimodal curation at petabyte scale into a product that enterprise AI teams love to use. You'll partner closely with the founders, our research, engineering teams to define what we build and why. This role will shape how Datology evolves from a technically differentiated platform into a category-defining AI tooling company. WHAT YOU'LL WORK ON - Own the product roadmap end-to-end: from discovery and prioritization through launch and iteration, with a focus on enterprise-grade AI tooling - Partner with research and engineering to turn ambiguous, early-stage outputs into concrete, shippable product decisions. - Define and drive the enterprise product experience -- including platform UX, API design, deployment flexibility (BYOC, on-prem), and integrations with existing ML workflows - Develop deep customer intuition by engaging directly with enterprise ML teams, data scientists, and infrastructure engineers -- turning their pain points into a clear product strategy - Build the foundational PM infrastructure: discovery frameworks, roadmap tooling, release processes, and cross-functional rituals that scale as the team grows - Work with Sales and Customer Success to ensure the product enables a repeatable, defensible go-to-market motion - Track the competitive landscape across AI tooling, MLOps, and data infrastructure to inform positioning and prioritization - Serve as the connective tissue between research output and commercial product -- helping the team decide what to build, sequence how, and measure whether it's working ABOUT YOU - 5+ years of product management experience, with at least 3 years building enterprise software or AI/ML tooling at a senior or staff level - A strong technical foundation. You can read a research paper, engage credibly with ML engineers about training pipelines and data infrastructure, and distinguish meaningful technical differentiation from noise - You've shipped products where the starting point was a paper or prototype and know how to impose structure without killing what makes the technology special - Experience as a founding or early PM, with a track record of building product functions and processes - Deep familiarity with the enterprise AI/ML buyer: you understand how ML teams evaluate tools, what makes them adopt and stick, and how infrastructure decisions get made - A sharp product instinct for developer and technical user experiences. You know the difference between a product that's powerful and one that's actually used - Excellent cross-functional communication: you can make a research result legible to a sales team and a customer complaint actionable for an engineer - Comfort operating in ambiguity and a bias toward decisive, data-informed action Bonus points if you have: - Hands-on experience with model training, data pipelines, or MLOps workflows - Prior experience at an AI infrastructure, developer tools, or data platform company - Exposure to enterprise procurement and compliance requirements (BYOC, on-prem, data sovereignty) Don’t meet every single requirement? We still encourage you to apply. If you’re excited about our mission and eager to learn, we want to hear from you! COMPENSATION At DatologyAI, we are dedicated to rewarding talent with competitive salary and meaningful equity. The salary for this position ranges from $215,000 to $300,000. - Starting pay is based on job-related skills, experience, qualifications, and interview performance. Benefits: - 100% covered health benefits (medical, vision, and dental). - 401(k) plan with a generous 4% company match. - Unlimited PTO policy - Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility. - Annual $2,000 wellness stipend. - Annual $1,000 learning and development stipend. - Daily lunches and snacks are provided in our office! - Relocation assistance for employees moving to the Bay Area.

Listed by DatologyAI for a position based in the United States. Employers on this board attest they are hiring domestically.

Engineering

174 days ago

Software Engineer, Front-end

DatologyAI · Redwood City, California, USA

Pay

$180k–300k

Setting

On-site

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Listed by DatologyAI for a position based in the United States. Employers on this board attest they are hiring domestically.

Engineering

241 days ago

Software Engineer, Cloud Infrastructure

DatologyAI · Redwood City, California, USA

Pay

$180k–300k

Setting

On-site

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ABOUT THE COMPANY Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy. At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling (BeyondWeb https://www.datologyai.com/blog/beyondweb) and pretraining with domain-specific data (The Finetuner’s Fallacy https://www.datologyai.com/blog/finetuners-fallacy). We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models. Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data. This role is based in Redwood City, CA. We are in office 4 days a week. ABOUT THE ROLE We’re looking for an experienced Cloud Infrastructure Engineer to join our core team at DatologyAI. In this role, you will lead the design, build, and operation of highly available, secure, and scalable cloud infrastructure that powers our training, inference, and data curation pipelines. You’ll work closely with engineering, research, and product teams to define how we deploy and manage compute resources across AWS and other cloud providers. This role is a key early hire and offers an opportunity to have a deep technical and cultural impact. WHAT YOU'LL WORK ON - Architect and maintain our multi-cloud infrastructure (primarily AWS, potentially Azure/GCP), with a focus on reliability, security, and scalability - Define and implement infrastructure-as-code best practices using Terraform, CloudFormation, Pulumi (and similar technologies) - Design and manage Kubernetes-based systems for model training, inference, and data processing workloads - Optimize our CI/CD pipelines and streamline deployment of services across environments - Build monitoring, alerting, and logging systems to ensure high system availability and observability - Collaborate with research and engineering teams to provide infrastructure support for training large-scale ML models - Ensure our infrastructure supports various deployment models (cloud, on-prem, hybrid) for enterprise use cases - Drive cost-efficiency strategies across compute and storage resources - Respond to and resolve infrastructure-related incidents with a sense of ownership and urgency ABOUT YOU - 4+ years of relevant experience - You’ve led or helped build robust infrastructure systems at a startup or fast-moving engineering organization - Deep experience working with cloud providers (especially AWS), and ideally exposure to multi-cloud or hybrid-cloud setups - Strong with Kubernetes, Terraform, and containerized architectures - Confident with systems-level debugging—networking issues, memory leaks, resource bottlenecks, etc. - Comfortable writing clean, maintainable scripts in Bash, Python, or Go - You care deeply about building secure and scalable systems and take pride in reliable infrastructure - You’re collaborative, humble, and ready to own high-impact projects end-to-end Nice to Have - Experience supporting infrastructure for ML workloads (training pipelines, inference clusters, GPU orchestration) - Built or scaled infrastructure for teams working with large-scale datasets - Exposure to cost monitoring and optimization tools in cloud environments - Background supporting compliance and security in enterprise deployments COMPENSATION At DatologyAI, we are dedicated to rewarding talent with competitive salary and meaningful equity. The salary for this position ranges from $180,000 to $300,000. - Starting pay is based on job-related skills, experience, qualifications, and interview performance. Benefits: - 100% covered health benefits (medical, vision, and dental). - 401(k) plan with a generous 4% company match. - Unlimited PTO policy - Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility. - Annual $2,000 wellness stipend. - Annual $1,000 learning and development stipend. - Daily lunches and snacks are provided in our office! - Relocation assistance for employees moving to the Bay Area.

Listed by DatologyAI for a position based in the United States. Employers on this board attest they are hiring domestically.

Sales

242 days ago

Solutions Engineer (AI/ML, Pre-Sales)

DatologyAI · Redwood City, California, USA

Pay

$230k–300k

Setting

On-site

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ABOUT THE COMPANY Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy. At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling (BeyondWeb https://www.datologyai.com/blog/beyondweb) and pretraining with domain-specific data (The Finetuner’s Fallacy https://www.datologyai.com/blog/finetuners-fallacy). We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models. Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data. This role is based in Redwood City, CA. We are in office 4 days a week. ABOUT THE ROLE We are looking for a highly technical Solutions Engineer with deep ML and AI platform experience to support customers in a pre-sales role. In this role, you will partner closely with our most strategic prospects to deeply understand their data curation needs, technical constraints, and business goals, and to design scalable solutions that demonstrate the impact of DatologyAI’s platform. This role requires strong hands-on understanding of modern LLM/VLM training and evaluation. You will work directly with customer ML teams to design PoCs that connect data curation decisions to measurable outcomes in model quality, training efficiency, and downstream performance—across the full lifecycle of training (pre-training, mid-training, and post-training), and with rigorous evaluation plans and reporting. WHAT YOU’LL WORK ON - Embed deeply with strategic customers to understand their data curation needs, business challenges, and technical requirements in detail. - Lead end-to-end customer PoCs that connect data curation, training behavior, evaluation outcomes, including dataset analysis, training plan design, and results interpretation. - Partner with customer ML teams to map data & curation strategy - Design and execute evaluation plans for base and post-trained models, selecting appropriate benchmarks/metrics, and running model evaluations - Produce customer-ready evaluation reports: methodology, metrics, baselines, ablations (e.g., curated vs raw), conclusions, and recommended next steps for productionization. - Communicate technical results to both ML experts and exec stakeholders, including tradeoffs in compute, latency, and deployment cost. - Collaborate closely with GTM, Engineering, and Research teams to ensure seamless customer experiences, deliver compelling demos, align on requirements, and bring customer insights into actionable model training and product strategies. - Provide technical guidance, training, and clear documentation to ensure prospects can confidently assess the solution. ABOUT YOU - 4+ years of experience in software, ML platform, solutions, or customer engineering roles, with significant experience driving technical pre-sales engagements and PoCs. - Strong practical expertise in ML model training, including how models are trained and improved across pre-training, domain-specific mid-training, and post-training, such as supervised fine-tuning and reinforcement learning. - Demonstrated ability to design, run, and interpret model evaluations for base and post-trained models: choosing metrics/benchmarks, building or using evaluation harnesses, analyzing results, and presenting findings clearly with customers. - Examples of the kinds of practical deep learning questions you might have to answer for customers: - What’s the difference between MMLU, MMMU, and MMMLU? - Is SWE-Bench a useful eval for base models? - What’s a standard context window for pretraining, and what are the costs and benefits of changing it? - What’s the difference between CPT and midtraining? - Can we just compare your data to Qwen3? - Will your data work with our model architecture? - Strong programming skills in Python (or equivalent); able to prototype quickly and iterate with customers. - Experience with data processing / distributed systems (e.g., Spark, Ray, data lakes/warehouses) and comfort working with large-scale datasets. - Familiarity with modern ML infrastructure: PyTorch/Hugging Face ecosystems, distributed training concepts, and deployment environments across cloud/on-prem/hybrid. - Familiarity with cloud platforms (AWS/GCP/Azure) and containerization (Docker/Kubernetes). - Strong communication skills, with the ability to translate complex ML and systems topics for diverse audiences. - Required to travel to customer sites as needed to support pre-sales engagements. COMPENSATION At DatologyAI, we are dedicated to rewarding talent with competitive salary and meaningful equity. The salary for this position ranges from $230,000 to $300,000 OTE. - Starting pay is based on job-related skills, experience, qualifications, and interview performance. Benefits: - 100% covered health benefits (medical, vision, and dental). - 401(k) plan with a generous 4% company match. - Unlimited PTO policy - Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility. - Annual $2,000 wellness stipend. - Annual $1,000 learning and development stipend. - Daily lunches and snacks are provided in our office! - Relocation assistance for employees moving to the Bay Area.

Listed by DatologyAI for a position based in the United States. Employers on this board attest they are hiring domestically.

Sales

290 days ago

Forward Deployed AI Engineer (Post-Sales)

DatologyAI · Redwood City, California, USA

Pay

$230k–300k

Setting

On-site

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ABOUT THE COMPANY Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy. At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling (BeyondWeb https://www.datologyai.com/blog/beyondweb) and pretraining with domain-specific data (The Finetuner’s Fallacy https://www.datologyai.com/blog/finetuners-fallacy). We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models. Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data. This role is based in Redwood City, CA. We are in office 4 days a week. ABOUT THE ROLE We are looking for a highly technical, customer-obsessed Forward Deployed AI Engineer (Post Sales) to guide customers through deploying, operating, and adopting DatologyAI’s platform in complex on-prem or hybrid environments. You will become the trusted technical advisor for our most strategic customers, partnering closely with Sales, Research, and Engineering to drive successful deployments and long-term customer value. You'll bridge the gap between our core platform capabilities and the unique requirements of each customer's environment. This role is ideal for someone who thrives in ambiguity, enjoys solving challenging distributed systems problems, and wants to build both deep relationships and scalable solutions within a fast-moving startup. WHAT YOU’LL WORK ON - Lead customers through onboarding, deployment, and production rollout of DatologyAI’s platform while serving as the technical owner for assigned accounts—driving architecture, execution, long-term adoption, and tailored technical success plans. - Partner cross-functionally with Sales, Engineering, and Research to translate use-case requirements into actionable technical strategies, support early trials, relay customer feedback, and help shape roadmap priorities. - Guide customers in designing scalable, secure workflows across compute, storage, networking, and distributed systems, providing ongoing reporting on deployment progress, workload health, usage metrics, and executive-level updates. - Adapt and optimize DatologyAI’s platform across AWS, GCP, Azure, and on-prem Kubernetes environments, handling provider-specific APIs, storage systems, networking configurations, and compute orchestration—including tuning performance for network topology, storage tiering, and resource allocation in each environment. ABOUT YOU - 5+ years of experience in technical roles involving solution architecture, customer engineering, consulting, or technical program delivery. - Strong background in distributed systems, data infrastructure, and/or on-prem or hybrid compute environments. - Experience working with ML/AI workflows, designing or deploying systems involving Kubernetes, networking, data pipelines, or large-scale backend infrastructure. - Proficiency in Python, SQL, or similar languages, with the ability to contribute to technical conversations and debug customer issues end-to-end. - Experience leading complex technical projects with multiple stakeholders—translating business needs into clear architecture and execution plans. - Deep hands-on experience with multiple cloud platforms (AWS, GCP, Azure) including their compute, storage, networking, and IAM services. - Proven track record of adapting complex distributed systems to run across different infrastructure environments. - Expertise in infrastructure-as-code and configuration management for multi-environment deployments. - Required to travel to customer sites as needed to support critical deployments and customer engagements. COMPENSATION At DatologyAI, we are dedicated to rewarding talent with competitive salary and meaningful equity. The salary for this position ranges from $230,000 to $300,000. - Starting pay is based on job-related skills, experience, qualifications, and interview performance. Benefits: - 100% covered health benefits (medical, vision, and dental). - 401(k) plan with a generous 4% company match. - Unlimited PTO policy - Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility. - Annual $2,000 wellness stipend. - Annual $1,000 learning and development stipend. - Daily lunches and snacks are provided in our office! - Relocation assistance for employees moving to the Bay Area.

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