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Reflection AI

Builds AI models and deployment software

Member of Technical Staff - Pre-Training Evals Infra

Software EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

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 rather than just address symptoms.
  • 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 persistence in investigating subtle discrepancies in model outputs, evaluation results, and system behavior.

Responsibilities

  • Design and evolve evaluation abstractions by building clear APIs and data models for evaluation tasks, datasets, configurations, model outputs, and scores, making it straightforward to add new evaluations and extend existing workflows.
  • Build scalable, reliable execution infrastructure, including distributed systems 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 the provenance needed to reproduce results and investigate discrepancies.
  • Build researcher-facing tools, including intuitive interfaces and dashboards for inspecting model outputs, comparing checkpoints and experiments, and debugging unexpected behavior.
  • Operate and monitor evaluations as training progresses by tracking evaluation workloads and results, triaging failures, and developing alerts and diagnostics to distinguish changes in model quality from inference or evaluation issues.
  • Partner directly with researchers to identify bottlenecks, prioritize high-impact improvements, and turn bespoke workflows into reusable self-service tools that work across teams.

About the Company

Reflection AI

Builds AI models and deployment software

Reflection AI develops language models for software developers, companies and governments that want control over how AI is deployed and adapted. Its research concentrates on coding, reasoning and AI agents that work through tasks with software tools. The lab builds the surrounding software and infrastructure as well as models, letting customers run AI through its hosted platform or in their own computing environments. Its commercial work pairs model access with engineers who design applications and support customized enterprise deployments from development through operation. Reflection AI was founded in 2024 and is headquartered in New York City.

Company size
201-500
Company stage
Late Stage VC
Total funding
$4.6B
Headquarters
New York City, New York
Founded
2024

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