Staff Research Engineer/Scientist

What you'll do

• Lead end-to-end research projects in agent learning and recursive self-improvement, from hypotheses and experiments to measurable improvements.
• Build training environments, benchmarks, evaluation methods, and reproducible pipelines for agent training, rollout, and inference.
• Partner with research, engineering, and product teams to move validated methods into reliable enterprise systems and communicate findings.

What they ask for

• 7+ years of relevant ML/AI research or engineering experience, or equivalent evidence of research depth and impact; a PhD or other advanced degree is required.
• Strong foundations in machine learning, deep learning, reinforcement learning and/or probabilistic/statistical experimentation, with hands-on experience training or adapting large language models or multi-modal models.
• Advanced Python and PyTorch skills; practical depth in agentic AI and experience designing decision-useful evaluations.
• Experience with distributed training, rollout, and/or inference using relevant systems, plus strong software engineering fundamentals.

Nice to have

• Research or production experience in multimodal, document AI, computer vision, speech/audio, multilingual, or cross-lingual modeling.
• Experience with enterprise agents, synthetic data, automated experimentation, GPU clusters, or research impact through shipped capabilities, publications, patents, benchmarks, or open-source contributions.

Pay

$202,500 - $354,400 USD base salary

Tools

Python, PyTorch, PyTorch distributed/FSDP, DeepSpeed, Megatron, verl, TRL, OpenRLHF

AI focus

Research and develop enterprise agents, including model post-training, agent harnesses, recursive self-improvement, training environments, evaluation, and multimodal capabilities.