Autonomous AI R&D Systems Engineer

Thesis (YC F25); San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Thesis in San Francisco is seeking a highly capable Member of Technical Staff to build an autonomous AI research system. You will work on frontier evolutionary search, large-scale GPU orchestration, and end-to-end AI pipelines to accelerate discovery.

You should have a strong ML foundation, graduate degree preferred, and experience with distributed systems, Python, and Rust. You will ship robust experiments at scale and contribute to AI for science across biology, chemistry, and physics.

Qualifications

• Deep foundations in ML or related quantitative field.
• Experience with automated discovery methods is a plus.
• Strong math/statistics background preferred.

Responsibilities

• Autonomous AI R&D: Design an end-to-end AI system for automated hypothesis generation and model training.
• Evolutionary Search: Build algorithms that navigate large combinatorial spaces.
• Massively Parallel Systems: Build distributed GPU infrastructure for thousands of concurrent experiments.
• AI for Science: Apply AI research to biology, chemistry, and physics challenges.

Skills

Evolutionary Search

Reinforcement Learning

Systems Architecture

Applied Science

Python

Rust

Education

Graduate degree in ML/CS/Math/Stats/Physics

Job description

Thesis in San Francisco is seeking a highly capable Member of Technical Staff to build an autonomous AI research system. You will work on frontier evolutionary search, large-scale GPU orchestration, and end-to-end AI pipelines to accelerate discovery.

You should have a strong ML foundation, graduate degree preferred, and experience with distributed systems, Python, and Rust. You will ship robust experiments at scale and contribute to AI for science across biology, chemistry, and physics.