Technology and Transformation - EAD- Platform Engineer- Consultant/Senior Consultant

Role Overview:

We are seeking an experienced Platform Engineer with strong expertise in AWS, DevOps, AWS SageMaker, and Python. The ideal candidate will have 5+ years of experience and a proven track record in troubleshooting, supporting, and enabling developers and data scientists to deploy and manage their machine learning models in the AWS ecosystem efficiently.

Key Responsibilities:

• Collaborate with developers and data scientists to support the end-to-end deployment of machine learning models on AWS SageMaker and other AWS services.
• Design, develop, and maintain scalable infrastructure and CI/CD pipelines using AWS and DevOps best practices.
• Provide troubleshooting support to resolve issues in model deployment, performance, and infrastructure.
• Automate workflows for model training, testing, and deployment processes using Python and infrastructure-as-code (IaC) tools.
• Ensure the availability, performance, and security of the platform supporting data science workloads.
• Implement monitoring and logging solutions to identify and resolve issues proactively.
• Stay updated with the latest AWS services and recommend solutions to optimize workflows and infrastructure.
• Act as a liaison between data scientists, developers, and operations teams to streamline processes and enhance collaboration.

Key Requirements:

• 5+ years of experience as a Platform Engineer, DevOps Engineer, or a related role.
• Strong hands-on experience with AWS services, including but not limited to SageMaker, EC2, Lambda, S3, IAM, and CloudWatch.
• Experience in Containerization.
• Proficiency in Python, with the ability to create automation scripts and tools.
• Experience with DevOps practices such as CI/CD pipelines, version control (Git), and tools like Jenkins, GitLab, or Code Pipeline.
• Familiarity with containerization tools like Docker and orchestration platforms like Kubernetes (EKS).
• Excellent troubleshooting and debugging skills for infrastructure, deployment, and model performance issues.
• Understanding of machine learning model lifecycle and MLOps workflows.(Optional)
• Hands-on experience with Infrastructure-as-Code (IaC) tools like Terraform or CloudFormation.
• Strong communication and collaboration skills, with the ability to work closely with cross-functional teams.

Preferred Skills:

• AWS certifications (e.g., AWS Certified Solutions Architect, AWS Certified Machine Learning – Specialty).
• Experience with monitoring and logging tools like Prometheus, Grafana, or ELK Stack.
• Familiarity with data engineering workflows and tools.

What We Offer:

• An opportunity to work on cutting-edge machine learning projects with a collaborative and innovative team.
• A chance to make a significant impact by enabling data scientists and developers to deliver high-quality solutions on AWS.
• Competitive compensation, benefits, and professional growth opportunities.

Location: [Bangalore]

Employment Type: Full-Time