Member of Technical Staff - Pre-Training Evals Infra

Reflection • London, New York

1d • Onsite

About The Position

This role involves building the evaluation infrastructure that researchers use to understand model capabilities, guide training decisions, and assess readiness for release. The position spans evaluation authoring, distributed execution, and results analysis, with a particular focus on pre-training. The individual will work directly with researchers to make evaluations faster, more reliable, and easier to use, ensuring that the results accurately reflect the models being evaluated.

Requirements

• Strong proficiency in Python, C++, or Rust, with the ability to reason deeply about concurrency, memory behavior, and performance.
• Experience designing, building, and operating reliable, maintainable distributed systems, with sound judgment about interfaces, failure modes, and architectural tradeoffs.
• Working knowledge of model inference and evaluation, including how implementation and configuration choices can affect measured model quality.
• Ability to investigate complex problems across system boundaries, follow evidence, and identify root causes.
• Strong product judgment and experience translating the needs of researchers or other technical users into clear APIs and usable tools.
• Comfort owning ambiguous problems end to end, prioritizing competing research needs, and balancing rapid delivery with long-term reliability and maintainability.
• Attention to detail and the persistence to investigate subtle discrepancies in model outputs, evaluation results, and system behavior.

Responsibilities

• Design and evolve evaluation abstractions, building clear APIs and data models for evaluation tasks, datasets, configurations, model outputs, and scores.
• Build scalable, reliable execution infrastructure for evaluating model checkpoints throughout training and ahead of release, with robust orchestration, observability, and recovery from failures.
• Optimize evaluation and inference performance by profiling inference servers and distributed execution to improve throughput, GPU utilization, and time to results.
• Establish evaluation correctness and reproducibility by building validation and regression tests, versioning datasets and configurations, and preserving provenance.
• Build researcher-facing tools, creating intuitive interfaces and dashboards for inspecting model outputs, comparing checkpoints and experiments, and debugging unexpected behavior.
• Operate and monitor evaluations as training progresses, tracking workloads and results, triaging failures, and developing alerts and diagnostics.
• Turn research needs into reusable systems by partnering directly with researchers to identify bottlenecks, prioritize improvements, and convert bespoke workflows into self-service tools.

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: We have regular off-sites, happy hours, and team celebrations.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed