Member of Technical Staff, Data Flywheel

Highlights

• Close the gap between benchmark scores and real-world model performance.
• Turn live model usage into rigorous evals and targeted training data.
• Build pipelines to ingest, version, and evaluate data reliably at scale.

What they offer

• Top-tier compensation: salary and equity structured to recognize and retain talent globally
• Stock options for everyone who joins and contributes to Reflection's success
• Comprehensive medical, dental, vision, and life insurance with annual wellness allowance
• Lunch and dinner provided in the office daily
• 22 weeks paid parental leave for all new birthing and non-birthing parents
• Unlimited paid time off in the U.S. and 30 days in the U.K.
• Visa sponsorship and long-term immigration pathway support
• Regular off-sites, happy hours, and team celebrations

Ideal candidate

High-agency builder who thrives in ambiguity and owns projects end to end. You love turning messy real-world model behavior into measurable progress and collaborating across research, engineering, and partners.

Requirements

• 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 areas such as 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