Fundamental is an AI research lab pioneering the future of enterprise decision-making. Our flagship model, NEXUS is the world's most powerful Large Tabular Model (LTM) - purpose-built for the structured records that contain trillions of dollars in business value. With $275m in funding from leading investors and trusted by Fortune 100 companies, Fundamental is 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 roleIn this role, you'll develop, and productize data science capabilities that enhance and expand our product performance on real enterprise use cases - working across a wide range of prediction tasks, data types, and business domains. You'll go deep on hard data science problems, collaborate closely with R&D on product capabilities, and ship production-grade work that has a direct impact on Production use cases.
Key responsibilities
Own the reliability, performance, and scalability of Extensions capabilities end to end
Design and build distributed workflows that are efficient, reproducible, and observable in production
Collaborate closely with Data Scientists on the team to deeply understand requirements and translate them into engineering decisions
Identify and resolve performance bottlenecks, ensuring Extensions capabilities meet the latency and throughput demands of enterprise deployments
Contribute to architectural decisions around how Extensions integrates with the broader NEXUS backend
Write clean, well-tested Python code and hold a high bar for code quality across the team
Contribute to internal engineering documentation and help establish best practices for backend development within the team
5+ years of backend engineering experience, with a strong focus on Python
Excellent Python skills - you write clean, idiomatic, well-tested code and know the language deeply
Solid experience designing and operating distributed systems at production scale
Strong understanding of concurrency, task execution, and workflow orchestration patterns
Experience building systems that are reproducible, observable, and easy to debug in production
Ability to work closely with non-engineering counterparts and translate complex requirements into reliable implementations
Strong ownership mindset - you drive work end to end and care about outcomes, not just output
Hands-on experience with workflow orchestration systems such as Temporal, Dramatiq, Celery, or equivalent
Familiarity with ML infrastructure or experience working alongside data science teams
Experience with high-throughput data processing pipelines
Exposure to Kubernetes and container-based deployment environments
Background in performance profiling and optimization of Python services
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
