Description
We are seeking a Vice President-ML Ops Engineer to lead the design, implementation, and governance of enterprise-grade ML Ops frameworks that enable scalable, secure, and efficient deployment of AI and Generative AI models.
The successful candidate will play a pivotal role in managing operations within a business area and maintaining processes with risk management initiatives.
Key responsibilities include:
- Leading and mentoring a high-performing ML Ops engineering team
- Architecting and governing scalable, secure, and cost-optimised AWS platforms for enterprise ML and GenAI workloads
- Designing and implementing automated ML pipelines covering data ingestion, management, feature processing, and high-throughput model training/inference workflows
- Establishing robust data and model governance frameworks
- Building comprehensive model observability and monitoring systems
- Driving security, reliability, and operational excellence
Technical skills required for this role include:
- Experience in Programming & Automation: Python, Bash, SQL
- MLOps Tools: MLflow, Kubeflow, AWS SageMaker Pipelines
- Cloud Platforms: AWS (SageMaker, Bedrock, Lambda, Step Functions, CloudWatch)
- DevOps Expertise: CI/CD (GitHub Actions, Jenkins), Docker, Kubernetes
- Data Management: Enterprise data governance, ETL processes
- Leadership Skills: Strategic planning, team management, stakeholder communication