Senior MLOps Engineer (Training & Inference Optimization)

We are seeking a Senior MLOps Engineer to steer the technical vision of our Training and Inference Optimization team, architecting the infrastructure that powers our next-generation AI models, and optimizing large-scale LLM training and deployment. As a Senior MLOps Engineer, you will bridge the gap between systems programming and machine learning, optimizing GPU utilization, managing complex checkpointing strategies, and implementing automated fault tolerance for long-running jobs.

Requirements

• 5+ years in MLOps, DevOps, or Software Engineering
• Expert-level proficiency with PyTorch and the NVIDIA stack (CUDA, NCCL, Triton)
• Hands-on experience with NVIDIA NeMo (or Megatron-Bridge) for distributed training and at least two of the following for serving: vLLM, TensorRT-LLM, or SGLang
• Proven experience with SLURM/Flyte/Ray/SkyPilot for cluster management and MLflow (or similar tool) for experiment and model management
• Deep expertise in Kubernetes and K8s operators (e.g., KubeRay, MPI Operator, or Run:ai)
• Mastery of Python and a functional understanding of C++ or Rust for performance-critical components

Benefits

• Multiverse Computing is committed to building an inclusive workplace
• Equal opportunity employer
• Welcomes people from all different backgrounds