Software Engineer - ML Infrastructure (US)

We are looking for an ML Infrastructure Engineer with 6+ years of experience to come in and establish best practices for our distributed training, reinforcement learning, and inference systems. You'll be a senior, autonomous engineer who can teach the team what ML infrastructure looks like, someone who's operated at scale at a top-tier engineering organization and is ready to own the systems that power our foundation models. This is a ground-floor opportunity at a 5-person team backed by Bedrock Capital, Trust Ventures, and Jack Altman, building the first radiology-as-a-service platform powered by a multi-modal AI copilot to solve a crisis that leads to 200k deaths per year.

What will you be doing?

• Own and build the distributed training infrastructure for foundation models on large-scale medical imaging, including parallelism and checkpointing for volumetric data

• Design and operate the reinforcement learning training stack, high-throughput rollout generation, reward-model serving, and experience collection at scale

• Partner directly with researchers (ex-DeepMind, ex-Meta) to understand their workflows, prototype new ideas, and translate them into production-ready systems

• Build high-throughput data loading and preprocessing pipelines that keep GPUs saturated on large volumetric and multimodal datasets

• Contribute to production serving and deployment pipelines, including model rollout, canary deployments, and monitoring