Embedding VC
Member of Technical Staff, Applied Research
New York, NY · Hybrid · Staff · Full-time · Posted Oct 16, 2026
- Experience
- No hard rule; roughly 3–5 years is envisioned, but more or less experience is acceptable.
- Education
- Master's / PhD-level knowledge of machine learning fundamentals.
About the job
Build post-training workflows, agent environments, high-quality training data, evaluation and reward systems, and research infrastructure for frontier AI labs.
What you'll do
- Design and run model improvement workflows, including fine-tuning, preference optimization, and reinforcement learning.
- Create agent tasks, environments, trajectories, reward signals, validators, and evaluation tools.
- Run training experiments on distributed GPU clusters and develop infrastructure for training, evaluation, and data generation.
What they ask for
- Master's- or PhD-level knowledge of machine learning fundamentals, including linear algebra, optimization, and stochastic gradient descent.
- Hands-on experience with or deep understanding of LLM fine-tuning, preference data, reward modeling, or reinforcement learning for language models.
- Strong Python skills and comfort building with PyTorch, FastAPI, and modern ML infrastructure.
- Strong engineering judgment to work across research ambiguity and production constraints.
Nice to have
Tools
GRPO, PyTorch, FSDP, FastAPI, Python
AI focus
Applied AI research focused on post-training, agent environments, training data, rewards, and evaluation for frontier models.
Model-written summary · the original posting is authoritative