Software Engineer, Applied AI

Partner closely with frontier AI labs to understand their data, post-training, and evaluation needs

Build and operate scalable data pipelines for post-training workflows and model evaluations

Design and build scalable systems for synthetic data generation and data quality, and work directly with customers to understand requirements and develop technical solutions

Prototype new data types, benchmarks, and evaluation frameworks

Lead technical discussions with customers

Direct frontier exposure. You’ll work closely with researchers at leading AI labs, building infrastructure that directly accelerates cutting-edge research.

Coding + customer work. This role blends deep technical execution with customer interaction. Engineers who enjoy both building and communicating tend to thrive.

Fast-moving, high-ownership environment

Technically demanding, collaborative work

“Building the plane while flying it”

In-person culture (SF, 181 Fremont)

Aligned with frontier research timelines

Strong backend engineering fundamentals in a modern language (Python, Go, Rust, etc.)

Experience with model training and inference

Strong grounding in statistical analysis and experimental design for measuring model performance and improvements

Familiarity with evaluation methods for large language models

Comfort working through ambiguity and shipping iteratively

Enjoys ownership and customer-facing problem solving

Thinks entrepreneurially and moves quickly

Balances speed with engineering rigor

Communicates clearly with technical and non-technical users

Direct exposure to frontier AI research

Real ownership and visible impact

Technical depth paired with human interaction

Fast feedback loops and high leverage

There are very few roles that combine this level of technical rigor, customer proximity, and research exposure.