Senior ML Systems Engineer, Frameworks & Tooling

Job summary

Responsibilities

We’re looking for a senior engineer to help build, maintain and evolve the training framework that powers our frontier-scale language models. This role sits at the intersection of large-scale training, distributed systems, and HPC infrastructure.

• Building a high-performance data loading and caching pipeline.
• Implementing performance profiling across the ML systems stack
• Developing internal metrics and monitoring for training runs.
• Building reproducibility and regression testing infrastructure.
• Developing a performant fault-tolerant distributed checkpointing system.

What they're looking for

• Strong engineering experience in large-scale distributed training or HPC systems.
• Experience with multi-node cluster orchestration (Slurm, Ray, Kubernetes, or similar).
• Comfort debugging performance issues across CUDA/NCCL, networking, IO, and data pipelines.
• Experience working with containerized environments (Docker, Singularity/Apptainer).
• A track record of building tools that increase developer velocity for ML teams.

Tech stack

• Node.js
• JAX
• Ray
• Kubernetes
• CUDA
• Docker
• PyTorch
• vLLM