Engineering manager - AI platform

Tasks

• Build MLOps components for ML lifecycle
• Collaborate with AI researchers and engineers
• Design build and maintain scalable AI platform
• Develop data governance and security best practices
• Lead and mentor software engineers
• Manage MLOps tools and integrations
• Monitor and improve training deployment and operations
• Optimize compute resources scheduling and costs
• Own product roadmap for AI platform

Perks/Benefits

• Career growth
• Flexible scheduling
• Hybrid work environment
• Occasional travel
• Professional development

Skills/Tech-stack

AWS | Agent systems | Argo | Azure | CI/CD | Cloud Computing | Distributed Systems | Docker | GCP | Go | Infrastructure as Code | JAX | Kubeflow | Kubeflow Pipelines | Kubernetes | LLMOps | MLOps | MLflow | Multi-Agent | Multi-Agent Systems | PyTorch | Python | Reinforcement Learning | TensorFlow | Terraform | “as-code”