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Research Engineer
Full-Time · San Francisco
You will train the models that go into production at Conway's largest customers. The work spans training, finetuning, and evals to run models against real-time data at scale. You will also spend time with the customers, understanding their data, constraints, and feedback.
Sample projects include:
- • Train models on a customer’s production data
- • Build an information-theoretic eval suite that measures how well learned detectors perform in new contexts
- • Develop representation learning techniques that make inference tractable in high-dimensional regimes
Requirements:
- • Deep formal training in statistics, mathematics, or physics, or equivalent research experience
- • Hands-on experience training models at scale. You have written training loops that run on more than one GPU and debugged them when they broke
- • Comfort reading unfamiliar codebases, data, and customer environments
Nice to haves:
- • Experience training or fine-tuning language models in production
- • Background building RL environments, eval frameworks, or agent systems
- • First-author publications at NeurIPS, ICML, ICLR, or comparable venues
- • Founder or early engineer at a zero-to-one company