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

In 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

Must have

• 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

Nice to have

• 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

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