Senior/Staff Software Engineer

Responsibilities

• Lead design, implementation, and operation of training performance optimizations for VLM, VLA, and foundation-model training.
• Own the technical strategy and multi-quarter roadmap for reinforcement-learning frameworks and performance optimization.
• Profile and diagnose throughput bottlenecks across compute, compiler, framework, and cluster-networking layers.
• Partner with ML researchers, data engineers, and hardware engineers on requirements and architectural decisions for large-scale training infrastructure.
• Build custom kernels and benchmarks to measure and validate performance improvements.
• Mentor engineers and raise the team’s technical bar through design reviews and best practices.

Requirements

• 7+ years of total experience, including 4+ years working on large-scale model training platforms and leading projects end to end.
• Deep experience with distributed training frameworks such as Megatron-LM and TorchTitan, and efficient use of GPU or accelerator clusters at scale.
• Experience with RL frameworks such as Verl and MILES and algorithms including GRPO and PPO.
• Experience with collective communication libraries such as NCCL and optimizing communication/compute overlap in multi-node training.
• Strong command of profiling tools including NVIDIA Nsight, PyTorch Profiler, or XLA/JAX profiling.
• Proficiency in Python or C++.
• Experience with ML compilers, performance tooling, or hardware/software co-design involving GPU, TPU, or accelerator architectures.
• Ability to influence across teams and communicate technical tradeoffs to researchers and engineers.