19 days ago
San Francisco, CA, USAMid Level
Base Salary
$164k - $215k/yr
Responsibilities
- Execute scoped post-training research and engineering projects from experiment design through evaluation and implementation.
- Train and evaluate reward and preference models using professional design decisions.
- Apply supervised fine-tuning, distillation, preference optimization, and reinforcement learning methods.
- Design rigorous evaluations for validity, reproducibility, and research prioritization.
- Translate research results into production systems with research and engineering partners.
- Partner with Product and Design to assess model performance in real workflows.
- Prototype emerging post-training techniques and contribute to reliable training and experimentation infrastructure.
- Document experiments, results, and learnings for the team.
Requirements
- Strong programming and software engineering skills, particularly for machine learning systems.
- Hands-on experience training or fine-tuning machine learning models.
- Experience with generative models, including diffusion or flow models, through professional work, research, or substantial technical projects.
- Familiarity with supervised fine-tuning, preference optimization, reward modeling, distillation, or reinforcement learning.
- Experience designing experiments and evaluating model performance.
- Strong machine learning fundamentals and the ability to turn research ideas into working implementations.
- Interest in product-coupled research and comfort solving open-ended technical problems.
- Collaborative research and engineering approach, including documenting results and incorporating feedback.
- Preferred qualifications include experience with high-performance training or inference systems, large-scale training infrastructure, preference data or human-feedback systems, and moving ML experiments toward production.
- Interest in industrial design, physical products, or the people who make them is preferred.
Benefits
- 100% employer-sponsored medical coverage for employees and 25% dependent coverage, plus dental, vision, and mental health benefits.
- Meaningful equity ownership, flexible PTO, 401(k) with employer match, paid parental leave, and an annual Learning & Development allowance.
- Weekly catered lunch at the San Francisco headquarters and a monthly gym membership stipend.
- In-person, full-time role based in San Francisco, California.
Categories
AI ResearchML Engineering