Member of Technical Staff, Data Flywheel
Reflection· Research
New York, NY, San Francisco, CA, London$0Full-timePosted 2mo ago
About the role
The Data Flywheel team builds signals, data, and feedback loops to turn model usage into rigorous evaluations, targeted training data, and measurable improvements in future model generations. This is a hands-on technical role at the intersection of research and deployment, collaborating with researchers, engineers, customers, partners, vendors, and the open-source community to move from observation to validated improvement.
Responsibilities
- Identify high-value data sources and partnership opportunities, deeply understand the underlying use cases, and translate them into representative evaluations
- Bring new data sources online, from initial partner conversations and data scoping through quality validation and integration into production evaluation and training pipelines, where appropriate
- Design and build evaluations, graders, and feedback loops that make priority real-world model behaviors measurable
- Analyze model performance and failure modes, then translate those insights into targeted datasets, reward signals, and training interventions
- Develop human and synthetic data strategies for capabilities where existing data is insufficient, including designing and running evaluation and data-collection programs with vendors
- Build the infrastructure and pipelines needed to ingest, inspect, version, and evaluate data reliably at scale
- Collaborate closely with pre-training, post-training, applied, and partnership teams to turn new signals into measurable model improvements
Qualifications
- Degree (BS, MS, or PhD) in Computer Science, Machine Learning, or related discipline, or equivalent practical experience
- Deep technical understanding of LLM training and evaluation, with hands-on experience in evaluation design, data curation, reinforcement learning, or reward design
- Strong software engineering skills and experience building automated data/evaluation pipelines or large-scale ML systems
- Track record of owning high-impact projects end to end, navigating ambiguity, and adapting quickly as priorities change
- Highly collaborative, action-oriented approach and excitement about defining how a new frontier lab measures and accelerates model progress
- High agency and thrive in a fast-paced startup environment; bias for impact over process
- Enjoy collaborating across research, engineering, operations, and product disciplines
Skills
Required:LLM training and evaluationData/infrastructure engineering
Benefits
- Top-tier compensation: Salary and equity structured to recognize and retain our talent globally
- Stock options: Everyone who joins and contributes to Reflection's success gets to share in the upside through stock options
- Health & wellness: Comprehensive medical, dental, vision, and life, with an annual wellness allowance
- Meals: Lunch and dinner are provided in the office daily
- Life & family: 22 weeks paid parental leave for all new birthing and non-birthing parents, including adoptive and surrogate journeys
- Vacation days: Unlimited paid time off in the U.S. and 30 days in the U.K
- Sponsorship support: We sponsor visas to help exceptional talent join our team and support long-term immigration pathways where applicable
- Team building: Regular off-sites, happy hours, and team celebrations
Last updated Oct 1, 2026. Interested? Apply on the company site.
About Reflection
Building frontier open intelligence
Building frontier open intelligence.
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