Research Engineer, 1X

• You must be scaling-pilled, and believe that scale will enable humanoid robots to exist, and be excited about being on the team that will make that happen for the first time in human history
• Python and/or C++ programming experience
• An intuitive understanding of training or inference scaling and what makes models run fast or slow

Desirable

• As a Research Engineer, Scaling, you'll build the systems that let every team and every robot go faster: training more often, evaluating more reliably, and deploying better models to our growing fleet
• You'll transform prototypes into production-scale infrastructure for learning and inference, enabling larger training runs and maximizing edge compute utilization to make our models more capable
• High agency and ownership on scaling capabilities in distributed training and/or inference
• Ensure that compute is never the bottleneck, i.e. we always have more compute available than data
• Enable large-scale (1000+ GPU) training on billion frames+ of robot data, from fault tolerance to distributed ops to experiment management
• Optimize high-throughput datacenter scale distributed inference for world models: work on the world's fastest diffusion inference engine
• Improve low-latency on-device inference for a variety of robot policies with quantization, scheduling, distillation and more
• Here are some example projects you might work on at 1X. If you have direct experience in solving one of the "sample projects" listed below, please let us know in your cover letter
• Quantizing, pruning, distilling, and optimizing a model to run as fast as possible on a given hardware SKU
• Creating or contributing to large-scale, high-throughput inference engines for diffusion models or LLMs, like xDiT, SGLang, vLLM, or TensorRT-LLM
• Training large models on hundreds to thousands of GPUs, and designing the infrastructure to scale small experiments to large production runs

• Target start date: Immediately
• The team reviews your CV and statement of exceptional work
• 15 minute phone conversation with our talent acquisition team
• 45-minute virtual interview with a team member asking a coding question in the language of your choice
• On-site interview (in-person or virtual) consisting of 4 technical interviews (mix of coding, systems design, open-ended research interview)
• Background reference checks
• Offer