MLOPs Infrastructure Lead

Your Role

• Design and implement scalable, cloud-native MLOps infrastructure to support the entire ML lifecycle, from experimentation to production deployment
• Help develop IAC scripts for required Infra provisioning
• Establish best practices for ML infrastructure monitoring, logging, and observability
• Collaborate with MLOPS pipeline developers to understand their workflows and optimize infrastructure accordingly
• Drive technical decisions around tooling selection and infrastructure architecture
• Mentor junior engineers and provide technical leadership to the MLOps team

Your Background

Key ingredients for succeeding in this role are your:

• 7+ years of software engineering experience, with at least 3 years focused on ML/AI infrastructure Strong experience with cloud platforms (AWS/GCP/Azure) and container orchestration (Kubernetes) Expertise in infrastructure-as-code using tools like Terraform, CloudFormation
• Proficiency in Python and experience with ML frameworks (PyTorch, TensorFlow, etc.)
• Deep understanding of ML workflows, including training, experimentation, and deployment
• Experience with MLOps tools (MLflow, Kubeflow, Seldon, etc.) and CI/CD platforms (Jenkins, GitLab CI, etc.)
• Strong background in distributed systems and scalable architecture design
• Experience with monitoring and observability tools