Senior MLOps Engineer

We're hiring a Senior MLOps Engineer to lead the architecture and optimization of large-scale AI training and inference infrastructure.

You'll design distributed training pipelines, deploy high-performance LLM serving systems, optimize GPU utilization, and build scalable ML platforms using technologies such as PyTorch, NVIDIA NeMo, CUDA, Kubernetes, vLLM, TensorRT-LLM, SGLang, Ray, SLURM, and MLflow .

What we're looking for:

• 5+ years in MLOps, DevOps, or Software Engineering
• 2+ years working with LLM infrastructure
• Strong Python skills and experience with Kubernetes
• Expertise in distributed training, GPU optimization, and ML infrastructure
• Experience with NVIDIA AI software stack and high-performance computing

This is an opportunity to shape the technical direction of next‑generation AI infrastructure while working on cutting‑edge LLM training and inference at scale.