Member of Technical Staff, Post-Training
Hybrid (San Francisco, CA), Hybrid (Remote (USA)), Hybrid (New York, NY), Hybrid (Mountain View, CA)$200k - $350kFull-timePosted 3mo ago
About the role
Role focused on designing and building post-training systems for frontier AI models, with high ownership and collaboration with researchers, domain experts, and customers. Early team member with influence over technical direction, emphasizing research capability, technical judgment, and builder mindset.
Responsibilities
- Design post-training systems and methodologies for frontier models, including supervised fine-tuning, reinforcement learning, preference optimization, reward modeling, and related approaches.
- Translate open-ended research or partner needs into clear hypotheses, experiments, evaluation plans, and production-quality implementations.
- Build and improve evaluation frameworks, benchmarks, training environments, data-processing pipelines, and quality-control systems.
- Run fast, rigorous iteration loops: prototype, evaluate, interpret results, and turn learnings into the next system or product.
- Partner directly with AI researchers and domain experts to develop high-signal data, feedback, and evaluation methods.
- Identify repeatable patterns across engagements and productize them into reusable software and platforms.
- Raise the technical bar through strong design judgment, clear communication, code quality, and mentorship.
- Contribute to the field through benchmarks, open-source tools, research, and technical writing where it creates leverage.
Qualifications
- 3+ years of demonstrated strength in post-training, fine-tuning, or model-evaluation work. Relevant experience may include RL, SFT, LoRA/PEFT, full fine-tuning, RLHF, DPO, PPO, reward modeling, or training environments.
- Strong Python skills and the ability to write clean, efficient, scalable software.
- Hands-on experience with modern ML tooling, particularly PyTorch and large-scale data, training, or evaluation workflows.
- Sound experimental judgment: you can form hypotheses, choose meaningful metrics, diagnose failures, and distinguish signal from noise.
- Experience designing systems—not only implementing specifications—including the ability to make tradeoffs around quality, scale, reliability, and reuse.
- Comfort operating in an ambiguous, fast-moving environment with substantial ownership.
- Collaborative, low-ego communication and the ability to work effectively with researchers, engineers, domain experts, and customers.
Skills
Required:Post-training systems designPythonPyTorch
Benefits
- Ownership: Equity in a fast-growing company
- Financial Wellness: 401(k) match, competitive compensation, financial coaching
- Family Support: Paid parental leave, fertility benefits, parental coaching
- Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend
- Growth: $2,000 learning stipend, ongoing development
- Office: Commuting support, free lunch, and gym in our SF office
- Time Off: Flexible PTO, 15 holidays + 2 flex days
- Connection: Team outings & referral bonuses
Last updated Oct 1, 2026. Interested? Apply on the company site.
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