Thinking Machines LabSan Francisco, CABuild and operate research infrastructure like evaluation frameworks, RL training systems, experiment tracking, and visualization tools. Partner directly with ML researchers to identify bottlenecks, ensure high adoption, and accelerate research velocity. Requires strong software engineering skills and Python/Rust proficiency.
Minimum qualifications:
Preferred qualifications:
Build and own ML infrastructure, data pipelines, and tooling for Safeguards research at Anthropic. Focus on fast researcher iteration for training/evaluating lightweight detectors on model internals while ensuring correctness at scale. Requires strong Python, distributed systems, and production infrastructure experience.
Build and operate research infrastructure like evaluation frameworks, RL training systems, and experiment tracking platforms. Partner directly with ML researchers to identify bottlenecks, ensure high adoption of tools, and accelerate research velocity.
Research engineer on the Safeguards Labs team building and evaluating novel safety methods to detect misuse, strengthen model safeguards, and reduce real-world harm from Claude.
Designs new information architectures for LLMs to interact with external data sources, implements finetuning/RL training, builds evaluation sets, and develops agentic search capabilities. Requires strong Python/ML skills and LLM experience.
Conducts research on visual perception, multimodal learning, and large-scale AI model training. Designs architectures, builds datasets and evaluations, and collaborates on frontier models. Requires ML expertise, Python proficiency, and experimental rigor.