AI Resident
San Francisco Bay Area$4k/moFull-timePosted 2mo ago
About the role
AI Resident at Ema in the Engineering department. You own one hard problem end to end, work with production data, and ship in a production codebase under mentorship. Projects focus on harness/inference-time work, post-training for agents, environments and rewards, data engines, evaluation, and efficiency within ML/agent systems.
Responsibilities
- You own one hard problem end to end. You write the proposal, build the system, design the evaluation, ship behind a gate, and finish with a write-up of what turned out to be true, including the parts that didn't work.
- Sit in the production codebase with a senior mentor and real production data.
- Recent residents have shipped self-improving harnesses, inference-cost work, agent memory, and eval infrastructure.
- Project gets scoped with you, not handed to you.
- Engage in harness and inference-time work, context engineering, tool and skill design, orchestration, and deciding where extra inference compute pays.
- Post-training for agents including SFT on curated trajectories, preference optimization, RL on real tasks, reward design, distilling frontier behavior into cheaper models.
- Create training/eval environments from enterprise workflows and manage rewards and defenses against reward hacking.
- Data engines: mining production agent steps for training/eval corpora, failure mining, labeling, synthetic augmentation.
- Evaluation: behavior-level benchmarks, LLM judges, reliability statistics for stochastic agents.
- Efficiency: routing, ensembles, caching, small-model specialization.
Qualifications
- No specific degree required. Strong undergrads, grad students, and self-taught builders welcome; demonstrated depth in ML or agent systems.
- Solid ML fundamentals and strong engineering: Python, PyTorch, and production-grade code shipping.
- Real depth in at least one of: post-training (SFT/DPO/GRPO-family RL), reward modeling/LLM judges, agent and tool-use systems, retrieval/memory, eval design.
- Statistical literacy and ability to size experiments; understanding that multiple samples with one seed are not definitive results.
- Honest measurement as a habit; prefer clean experiments over hunch-based shipping.
Skills
Required:ML fundamentalsPythonPyTorchExperiment design and statisticsCommunication and writing
Benefits
- Salary: $4,000 month
- SF Bay Area, on-site/hybrid, half/full-time term, flexible start
Last updated Oct 8, 2026. Interested? Apply on the company site.
About Ema
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