ML Infrastructure/MLOps Engineer

Responsibilities

• Deploy and optimize Ray + KubeRay for distributed data processing and model training across GPU clusters
• Build Kubeflow Pipelines for reproducible ML workflows, including data prep, training, evaluation, and deployment
• Configure MLflow for centralized experiment tracking and model registry
• Implement advanced job scheduling using tools like Kueue or Volcano for queue management and priority
• Build model CI/CD pipelines for automated training, validation, and canary/blue-green deployment
• Create self-service tooling for data scientists, including cluster provisioning and GPU allocation
• Monitor ML workload performance, focusing on GPU utilization and training throughput

Requirements

• 3–7 years of experience in ML infrastructure, MLOps, or ML platform engineering
• Strong expertise in Kubernetes (EKS preferred), including deployments, PVs, RBAC, and resource management
• Proficiency in at least two of the following: Ray/KubeRay, Kubeflow, MLflow, Airflow, or Argo Workflows
• Experience with distributed training frameworks such as PyTorch DDP, Horovod, DeepSpeed, or Ray Train
• Experience with model serving tools like KServe, Seldon, or custom FastAPI serving
• Strong Python engineering skills focused on automation and tooling rather than just notebooks
• Experience with GPU scheduling and resource management on Kubernetes

Benefits

• Learn from experts, including former AWS leaders and AI pioneers
• Direct ownership of high-impact "greenfield" projects from concept to global launch
• Work with modern technology, including the latest Generative AI frameworks and cloud-native architectures
• Build mission-critical systems used by major global enterprises
• Rapid career growth opportunities in a high-speed environment

About the Company

Aivar Innovations is an AI-first technology partner where cutting-edge technology meets industry expertise. We provide AI-augmented teams that accelerate development, reduce time-to-market, and deliver exceptional code quality for global enterprises.