MLOps Engineer

Our client are a global semiconductor company based.

Responsibilities:

• Architect Scalable Pipelines: Design and optimize distributed CI/CD workflows for complex, multi-language builds (C++, Python, and kernel-level code).
• Hardware-in-the-Loop (HIL) Automation: Automate the lifecycle of physical/virtualized accelerator clusters to validate code against real-world silicon performance.
• GPU/Accelerator Orchestration: Manage and scale containerized environments using Kubernetes and Helm, optimized for high-bandwidth compute tasks.
• MLOps Enablement: Build the infrastructure that allows researchers to deploy models without managing underlying software complexity.
• System Telemetry: Implement advanced monitoring for GPU utilization, thermal performance, and throughput regressions.

Key Requirements:

• Programming: Python and Bash for scripting; familiarity with C/C++ for performance optimization.
• CI/CD: Proven experience with GitHub Actions, Buildkite, or GitLab CI.
• Infrastructure: Hands-on experience with Terraform and Ansible (Infrastructure as Code).
• Orchestration: Strong Kubernetes (k8s) and Docker/Container lifecycle skills.

Desirable Skills:

• Accelerated Compute: Knowledge of CUDA, OpenCL, SYCL, or ROCm.
• Compilers/Frameworks: Experience with Triton, MLIR, PyTorch, or JAX.
• Inference/Scaling: Familiarity with vLLM, Triton Inference Server, or Slurm.