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Data Scientist (Forward Deployed)
Fundamental · United States
Pay
Not listed
Setting
Remote
About Fundamental
Fundamental is an AI company pioneering the future of enterprise decision-making. Founded by DeepMind alumni, Fundamental has developed NEXUS – the world's most powerful Large Tabular Model (LTM) – purpose-built for the structured records that actually drive enterprise decisions. Backed by world class investors and trusted by Fortune 100 companies, Fundamental unlocks trillions of dollars of value by giving businesses the Power to Predict.
At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI.
About the role
Fundamental is seeking a Forward deployed Data Scientist to facilitate the adoption of NEXUS and collaborate with customers to address complex technical challenges.
The Data Scientist is an integral part of our FDE team, which is dedicated to driving the successful deployment of Fundamental products and proving value over legacy baselines or net new use cases. They work hand-in-hand with customers from the Proof of Value stage to post-implementation, ensuring our solutions run securely in the client's production heartbeat.
In this role, you’ll manage customer relations involving multiple stakeholders (IT, C-suite, and data science teams) and function as a key bridge, translating field insights into our product roadmap.
Key responsibilities
You’ll individually help deploy into production use cases with considerable business impact, moving from "science experiments" to definitive ROI
You’ll work on rigorous head-to-head benchmarking against client baselines (XGBoost, LightGBM), executing the work of data engineering, feature engineering, and validation
You’ll work in collaboration with our research and product teams to translate operational pain points and data anomalies into essential inputs for the Fundamental roadmap
You’ll be involved in technical strategy to identify the right business problems, prevent data leakage, and handle the "last mile" integration (VPC, on-prem, air-gapped)
Your collaboration with the Sales and Solution Architect teams will help align diverse stakeholders and explain predictions to business users
Must have
You hold a PhD / master in CS / Math / Stats or you have equivalent deep statistical literacy
You have 2+ years as a technical individual contributor (data scientist or software engineer)
You have experience with containerization (Docker), orchestration, and writing performant APIs (FastAPI/Flask)
You master the end-to-end pipeline, from framing, pre-processing, ml algorithm and validation strategies
You have a deep understanding of data handling (PySpark, Pandas) and memory optimization
You have demonstrated experience optimizing models for a specific business problem
-
You hold strong communication skills with an ability to translate architectural nuances into clear business value
Nice to have
Experience with PyTorch and cloud-native ML pipelines (AWS, GCP, Azure)
Experience as a Forward Deployed Engineer, Staff Engineer, Machine Learning Engineer, or Staff Data Scientist
Industry-based subject matter expertise
Benefits
Competitive compensation with salary and equity
Comprehensive health coverage for you and your dependents, including medical, dental, vision, and 401K
Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys
Relocation support for employees moving to join the team in one of our office locations
A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action
Listed by Fundamental for a position based in the United States. Employers on this board attest they are hiring domestically.
Model Serving Engineer
Fundamental · United States
Pay
$95k–165k
Setting
Remote
ABOUT FUNDAMENTAL
Fundamental is an AI company pioneering the future of enterprise decision-making. Founded by DeepMind alumni, Fundamental has developed NEXUS – the world's most powerful Large Tabular Model (LTM) – purpose-built for the structured records that actually drive enterprise decisions. Backed by world class investors and trusted by Fortune 100 companies, Fundamental unlocks trillions of dollars of value by giving businesses the Power to Predict.
At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI.
ABOUT THE ROLE
Our Serving team is responsible for turning NEXUS, our Large Tabular Model, into a reliable and scalable production system. We own the infrastructure and execution stack that serves the model across multiple deployment environments, each with different requirements around scale, isolation, performance, and trust.
The team sits at the intersection of research and production engineering. We work closely with researchers to bring new model architectures into production, while building the systems needed to operate them efficiently and predictably under real-world workloads. Tabular foundation models introduce serving challenges that differ meaningfully from traditional LLM inference, including irregular computational behavior and complex resource tradeoffs across CPU, GPU, memory, and networking.
As a Model Serving Engineer, you’ll work across the full inference stack - from Python runtime performance and concurrency behavior to distributed orchestration, GPU serving infrastructure, and deployment architecture. You’ll identify bottlenecks, improve throughput and latency, and help define how new generations of the model are translated from research artifacts into production-grade systems.
This is a deeply technical, Python-heavy role for engineers who enjoy distributed systems, performance optimization, and low-level infrastructure challenges close to modern ML systems.
KEY RESPONSIBILITIES
- Optimize Python inference code for performance under real concurrency constraints, including GIL contention, multi-threading, multiprocessing, async execution, and long-running production workloads
- Work closely with research to understand model internals and support the continuous evolution of the architecture, especially around complex and non-obvious computational behavior under production load
- Collaborate with research and infrastructure teams to reason about hardware utilization and serving tradeoffs across GPU, CPU, memory, networking, batching, and concurrency
- Define and evolve the architecture behind our distributed inference and asynchronous execution stack, including orchestration, worker coordination, and end-to-end concurrency patterns
- Own the Triton serving layer for NEXUS, including how models are packaged, configured, and executed as part of our production inference pipeline
- Build observability and performance tooling across the serving stack, and use production metrics to drive tuning decisions around latency, throughput, and resource efficiency
- Solve cross-cutting serving challenges that emerge from deploying the same model across environments with very different scale, isolation, and reliability constraints
- Evaluate and integrate new inference runtimes, serving strategies, and infrastructure approaches as the model ecosystem evolves
MUST HAVE
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field (or equivalent practical experience)
- 5+ years of experience in model serving, ML infrastructure, or a closely related backend engineering role
- Deep expertise in Python concurrency, including GIL behavior, multi-threading, thread safety, multiprocessing
- Experience building asynchronous and message-driven systems
- High-performance, large-scale distributed systems
- Ability to read and reason about ML model implementations at a computational level, including compute behavior, batching, memory usage, and inference characteristics
- Experience profiling and optimizing performance across CPU, memory, I/O, and ideally GPU workloads, and translating findings into architectural improvements
NICE TO HAVE
- Understanding of GPU architecture, performance characteristics, and resource utilization in high-performance compute workloads
- Experience working with tabular and structured-data ML systems
- Understanding of neural networks and modern deep learning architectures
- Experience with Kubernetes and cloud infrastructure
- Familiarity with DevOps and production infrastructure tooling, including containers, Helm, observability, and CI/CD systems
BENEFITS
- Competitive compensation with salary and equity
- Comprehensive health coverage for you and your dependents
- Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys
- Relocation support for employees moving to join the team in one of our office locations
- A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action
Listed by Fundamental for a position based in the United States. Employers on this board attest they are hiring domestically.
Data Scientist (Forward Deployed)
Fundamental · United States
Pay
$135k–225k
Setting
Remote
ABOUT FUNDAMENTAL
Fundamental is an AI company pioneering the future of enterprise decision-making. Founded by DeepMind alumni, Fundamental has developed NEXUS – the world's most powerful Large Tabular Model (LTM) – purpose-built for the structured records that actually drive enterprise decisions. Backed by world class investors and trusted by Fortune 100 companies, Fundamental unlocks trillions of dollars of value by giving businesses the Power to Predict.
At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI.
ABOUT THE ROLE
Fundamental is seeking a Forward deployed Data Scientist to facilitate the adoption of NEXUS and collaborate with customers to address complex technical challenges.
The Data Scientist is an integral part of our FDE team, which is dedicated to driving the successful deployment of Fundamental products and proving value over legacy baselines or net new use cases. They work hand-in-hand with customers from the Proof of Value stage to post-implementation, ensuring our solutions run securely in the client's production heartbeat.
In this role, you’ll manage customer relations involving multiple stakeholders (IT, C-suite, and data science teams) and function as a key bridge, translating field insights into our product roadmap.
KEY RESPONSIBILITIES
- You’ll individually help deploy into production use cases with considerable business impact, moving from "science experiments" to definitive ROI
- You’ll work on rigorous head-to-head benchmarking against client baselines (XGBoost, LightGBM), executing the work of data engineering, feature engineering, and validation
- You’ll work in collaboration with our research and product teams to translate operational pain points and data anomalies into essential inputs for the Fundamental roadmap
- You’ll be involved in technical strategy to identify the right business problems, prevent data leakage, and handle the "last mile" integration (VPC, on-prem, air-gapped)
- Your collaboration with the Sales and Solution Architect teams will help align diverse stakeholders and explain predictions to business users
MUST HAVE
- You hold a PhD / master in CS / Math / Stats or you have equivalent deep statistical literacy
- You have 2+ years as a technical individual contributor (data scientist or software engineer)
- You have experience with containerization (Docker), orchestration, and writing performant APIs (FastAPI/Flask)
- You master the end-to-end pipeline, from framing, pre-processing, ml algorithm and validation strategies
- You have a deep understanding of data handling (PySpark, Pandas) and memory optimization
- You have demonstrated experience optimizing models for a specific business problem
- You hold strong communication skills with an ability to translate architectural nuances into clear business value
NICE TO HAVE
- Experience with PyTorch and cloud-native ML pipelines (AWS, GCP, Azure)
- Experience as a Forward Deployed Engineer, Staff Engineer, Machine Learning Engineer, or Staff Data Scientist
- Industry-based subject matter expertise
BENEFITS
- Competitive compensation with salary and equity
- Comprehensive health coverage for you and your dependents, including medical, dental, vision, and 401K
- Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys
- Relocation support for employees moving to join the team in one of our office locations
- A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action
Listed by Fundamental for a position based in the United States. Employers on this board attest they are hiring domestically.
Full-Stack Engineer
Fundamental · United States
Pay
$95k–220k
Setting
Remote
ABOUT FUNDAMENTAL
Fundamental is an AI company pioneering the future of enterprise decision-making. Founded by DeepMind alumni, Fundamental has developed NEXUS – the world's most powerful Large Tabular Model (LTM) – purpose-built for the structured records that actually drive enterprise decisions. Backed by world class investors and trusted by Fortune 100 companies, Fundamental unlocks trillions of dollars of value by giving businesses the Power to Predict.
At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI.
KEY RESPONSIBILITIES
As a Full-Stack Engineer at Fundamental, you will be responsible for developing both the front-end and back-end systems that allow users to seamlessly interact with our models. You will work on everything from the user interface to building scalable systems that power data upload and integration pipelines.
Your responsibilities will include:
- Building robust backend services and APIs for model inference, including efficient batching systems and optimization for large datasets
- Implementing state management and session persistence mechanisms to maintain model context and deliver consistent user experiences
- Designing and developing responsive, user-friendly frontends for model interaction, monitoring, and configuration using modern frameworks (React, Vue, or Angular)
- Designing event-driven architectures with pub/sub messaging patterns to enable asynchronous processing and system scalability
- Developing database connectivity layers and integration points with third-party data sources (e.g., Snowflake, Databricks)
- Creating comprehensive error handling, retry mechanisms, and monitoring solutions to ensure system reliability
- Collaborating with MLOps and DevOps teams to optimize the overall architecture and deployment pipeline
MUST HAVE
- 5+ years of experience in Full-Stack engineering roles
- Strong Python development experience, particularly with FastAPI and the ASGI ecosystem for high-performance API development
- Experience building full-stack applications with modern frontend frameworks (React, Vue, Angular) and backend systems
- Proficiency designing event-driven architectures using pub/sub messaging patterns and integrating distributed task queues (e.g., Celery) for asynchronous processing
- Understanding of model serving patterns (REST, gRPC, async batching) and experience handling large-scale inference workflows in production
- Knowledge of database systems (SQL/NoSQL) and integration with cloud data platforms (Snowflake, Databricks)
- Experience with state management, session persistence, and efficient data flow patterns in distributed applications
- Proven ability to deliver high-quality, maintainable frontend code and collaborate with design/product stakeholders
BENEFITS
- Competitive compensation with salary and equity
- Comprehensive health coverage for you and your dependents
- Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys
- Relocation support for employees moving to join the team in one of our office locations
- A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action
Listed by Fundamental for a position based in the United States. Employers on this board attest they are hiring domestically.
DevOps Engineer
Fundamental · United States
Pay
$105k–180k
Setting
Remote
ABOUT FUNDAMENTAL
Fundamental is an AI company pioneering the future of enterprise decision-making. Founded by DeepMind alumni, Fundamental has developed NEXUS – the world's most powerful Large Tabular Model (LTM) – purpose-built for the structured records that actually drive enterprise decisions. Backed by world class investors and trusted by Fortune 100 companies, Fundamental unlocks trillions of dollars of value by giving businesses the Power to Predict.
At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI.
KEY RESPONSIBILITIES
- Design and implement cloud infrastructure from the ground up
- Build and maintain Kubernetes clusters optimized for GPU workloads and ML applications, as well as Production SaaS hosting
- Implement GitOps practices using ArgoCD for continuous deployment
- Develop infrastructure as code using Terraform
- Create and maintain CI/CD pipelines for infrastructure and application deployment
- Implement monitoring and observability solutions for distributed systems
- Automate infrastructure management with Python and Bash
- Collaborate with ML engineers to optimize infrastructure for model training and serving
- Implement and maintain cost optimization strategies (FinOps) for cloud resources
- Monitor and optimize cloud spending, especially for GPU-intensive workloads
MUST HAVE
- 5+ years of experience in cloud infrastructure and DevOps
- 3+ years of experience with Python
- Strong experience with AWS and GCP cloud platforms
- Deep expertise in Kubernetes, including multi-cluster management, GPU workload optimization, resource scheduling and autoscaling, and network policies and security
- Experience with GitOps tools (ArgoCD preferred)
- Extensive experience with cloud networking, including VPC design, load balancer configuration, network security and segmentation, and cross-cloud networking solutions
- Strong CI/CD expertise, preferably with GitHub Actions
- Proficiency in infrastructure as code (Terraform)
- Experience with monitoring and observability tools
- Experience with FinOps practices and cloud cost optimization
NICE TO HAVE
- Experience with ML workflow tooling (MLflow, Kubeflow, or similar)
- Experience with FastAPI and Backend applications
- Familiarity with data platforms like Databricks or Snowflake
- Exposure to SRE practices or cloud security certifications
- Hands-on experience with Prometheus, Grafana, or Datadog
BENEFITS
- Competitive compensation with salary and equity
- Comprehensive health coverage for you and your dependents
- Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys
- Relocation support for employees moving to join the team in one of our office locations
- A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action
Listed by Fundamental for a position based in the United States. Employers on this board attest they are hiring domestically.
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