Applied Researcher - Scientific AI

What you'll do

• Build long-horizon research environments, tasks, evaluations, and reward signals from partner workflows and data.
• Design verifiers and develop RL and multi-agent methods; evaluate agents against baselines on held-out problems.
• Maintain reproducible experiments and release reusable environments, evaluations, and research code.

What they ask for

• Hands-on experience building and debugging model-training, post-training, agent, evaluation, or closely adjacent experimental loops.
• Strong experimental judgment, including meaningful baselines, trace inspection, and failure attribution.
• Strong Python and ability to build artifacts others can run, inspect, and extend.
• Comfort owning ambiguous problems and keeping partners and teammates informed.

Nice to have

• Prior work in autonomous research, ML for science, scientific computing, or reproducible computational research.
• Evidence of exceptional work such as publications, open-source systems, benchmarks, or shipped products.

Pay

$150-300k (base salary)

Tools

Python, RL

AI focus

Build and post-train agents for autonomous scientific research, using RL and multi-agent methods to formulate and test hypotheses, operate scientific tools, and choose experiments.