LEAD DATA ENGINEER - Machine Learning

About the Role

We are seeking a highly skilled candidate to lead the design, deployment, and management of enterprise-scale Machine Learning platforms and solutions on AWS. The ideal candidate will possess strong expertise in end-to-end MLOps, Machine Learning, and Python, with hands-on experience in AWS Bedrock and AWS SageMaker. This individual will serve as a Subject Matter Expert (SME), working closely with clients, data scientists, and engineering teams to operationalize AI/ML models in production environments.

• Design, build, and maintain end-to-end MLOps pipelines for ML model training, deployment, monitoring, and retraining.
• Develop scalable Machine Learning solutions using AWS cloud services.
• Implement and manage ML lifecycle workflows using AWS SageMaker and AWS Bedrock.
• Automate model deployment, testing, monitoring, and governance processes.
• Collaborate with Data Science, Data Engineering, and Cloud teams to deliver AI/ML solutions.
• Provide technical leadership and act as the MLOps SME for client engagements.
• Participate in architecture discussions, solution design, and technical consulting activities.
• Ensure high availability, security, scalability, and performance of ML platforms.
• Engage directly with clients to understand business requirements and provide technical guidance.

• 6-10 years of overall IT experience.
• Strong expertise in End-to-End MLOps.
• Hands-on experience in Machine Learning model development and deployment.
• Advanced proficiency in Python.
• Mandatory experience with:
  • AWS Bedrock
  • AWS SageMaker
• Experience with CI/CD, model versioning, monitoring, and automation frameworks.
• Strong communication and stakeholder management skills.
• Proven experience working in client-facing roles.
• Ability to work independently and drive technical decisions as an SME.

• Kubernetes
• Terraform
• Data Engineering concepts and pipelines
• Containerization and orchestration technologies
• Infrastructure as Code (IaC)

• Experience building Generative AI and LLM-based applications using AWS services.
• Strong understanding of cloud architecture, DevOps, and MLOps best practices.
• Experience in productionizing AI/ML solutions at scale.