…ABOUT THE ROLE This role focuses on keeping our frontier RL training runs fast, reliable, and unblocked. You will work across engineering and infrastructure…

…Fine-tuning or post-training (SFT, RLHF/DPO), RAG over proprietary technical data, or multi-agent orchestration - Deep software engineering: C++ or Rust, developer…

…and a dataset into a running training job — across SFT, LoRA adapter, and RL phases. Strong software engineering fundamentals; comfortable in Python and Bash…

…in software engineering Strong backend engineering fundamentals, especially in Python and distributed systems. Experience building production services, APIs, data pipelines, or ML infrastructure at…

…thermal systems in industrial or critical infrastructure environments Demonstrated track record of leading interdisciplinary research and engineering initiatives across teams or organizations Experience communicating…

…infrastructure for evaluation, training, or deployment Ability to work effectively across multiple codebases, teams, and organizations 8+ years of professional experience as a software…

…Research Engineer, Performance RL (Reinforcement Learning) — teaching Claude to write correct, fast code for accelerators Research Engineer, Universes — long-horizon, ultra-realistic agentic training…

…blog/frontier-rl-is-cheaper-than-you-think) - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https…

…blog/frontier-rl-is-cheaper-than-you-think) - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https…

…Training Infrastructure team builds a unified platform for large-scale LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post…

…blog/frontier-rl-is-cheaper-than-you-think) - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https…

Reality Labs Research (RL-R) brings together a diverse and highly interdisciplinary team of researchers and engineers to create the future of dexterous robotic…

…Surface findings to research and training teams to drive upstream model improvements. Minimum qualifications 8+ years of industry software engineering or ML engineering experience…

…We build the data, evaluations, and infrastructure that frontier labs use to train and judge their agents. We're looking for talented, experienced engineers…

…An insatiable appetite for learning and deeply engaging with modern ML/GenAI practices and infrastructure. Nice-to-Have Qualifications Engineering Roots: Strong software engineering…

…machine learning, software engineering, and biology — you'll directly improve model capabilities on scientific tasks through post-training, evaluation design, and RL environment development…

…Some weeks you'll be deep in pipeline or infrastructure engineering; others you'll be tuning prompts until the output is good, or sitting…

…Experience collaborating with software engineers, product managers, and business stakeholders. Strong communication skills and the ability to explain machine learning concepts and system behavior…

…Solid software engineering fundamentals — you can build research prototypes that others can run, extend, and integrate into data production workflows. Familiarity with ML infrastructure…

…end training pipelines. Experience with asset pipeline toolchains supporting URDF, MJCF, USD, or OpenUSD formats for robot and environment model management. Software Engineering IC4…

…Mentor mid-level and senior engineers on the MLOps team through code review, design review, and direct collaboration. Influence: Partner with the Training Infrastructure…

…We leverage Amazon's computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans…

…training internal engineering models on SpaceX data. This will consist of training models from scratch, fine tuning models, and using Reinforcement Learning (RL) to…

…Strong hands-on experience in AI software engineering with a focus on model training, fine-tuning, and machine learning systems Expert understanding of LLM…

…Foundation models (e.g., transformers, MoE, large-scale training) Generative world modeling (e.g., diffusion, autoregressive, hybrid approaches) Reinforcement learning (e.g., offline RL…