Senior Research Manager
$120k - $295k • Remote • San Francisco • FullTime
Posted 22d ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
AI Research Engineer
About the job
HUD is building reliable, fair, and open infrastructure for AI data, aiming to make data valuable for creators and trustworthy for AI trainers. We are a growing team of researchers, engineers, and operators backed by significant VC funding. We are seeking a Research Manager to lead research focused on enhancing HUD's agent training data and evaluations for frontier models. This role involves guiding research engineers through complex projects, translating findings into scalable methods, and staying technically engaged while ensuring rigorous experimentation and impactful results. The ideal candidate will possess a deep understanding of model training dynamics, including how signals, data, and evaluation design influence outcomes.
Responsibilities
- Set research direction for data quality, focusing on how training data impacts agent behavior and performance.
- Lead synthetic data efforts to understand efficient transformation of data types for training.
- Manage and mentor research engineers from problem definition to conclusion, fostering technical judgment.
- Design and review experiments linking model behavior and failures to data, environment, and reward design.
- Develop scalable methods for validating and improving training data, including audits and feedback loops.
- Collaborate with experts and vendors to translate research insights into improved workflows, tools, and standards.
- Communicate findings and tradeoffs to facilitate team prioritization and knowledge application.
Requirements
- Experience leading technical research projects from inception to completion.
- Experience managing and mentoring researchers or research engineers while staying technically involved.
- Strong understanding of machine learning and reinforcement learning, including how training objectives, data, and feedback shape model behavior.
- Experience with agent training data, evaluations, benchmarks, synthetic data, or model evaluation infrastructure.
- Sound experimental judgment to distinguish useful training signals from misleading metrics.
- Strong written communication skills for explaining methods and findings to diverse audiences.
- Experience building scalable data quality systems or validation pipelines for model training (preferred).
- Experience diagnosing subtle agent failure modes like reward hacking or grader errors (preferred).
- Experience translating research findings into tools and processes (preferred).
- Early-stage startup experience and strong communication skills (preferred).
Benefits
- Competitive compensation
- 100% covered top-of-the-line medical, dental, and vision (US and Singapore)
- Lunch and dinner for in-office employees
- Company-wide holiday break (Christmas Eve to New Year’s Day) on top of PTO and paid holidays
- Equinox membership (US)
- 401k (US)
- Commuter benefits (US)
- Health/wellness stipend (Singapore)
- Unlimited access to tokens for ChatGPT, Claude Code, Cursor, etc.
- Annual travel budget to visit offices