ML / Gen AI Engineer

JD Key Responsibilities :

Design, deploy, and manage scalable ML and GenAI workloads using AWS services including SageMaker Studio and Bedrock.

Implement and maintain infrastructure using AWS Lambda, EKS, ECS on Fargate, and EC2.

Collaborate with data scientists and ML engineers to operationalize ML models and GenAI pipelines.

Integrate and manage data platforms such as Databricks and Snowflake for AI / ML workflows.

Automate infrastructure provisioning and deployment using Terraform and Jenkins.

Develop and maintain Python-based automation scripts and ML / GenAI utilities.

Monitor, troubleshoot, and optimize cloud-based applications and services.

Ensure security, compliance, and cost-efficiency across cloud environments.

Required Skills & Qualifications :

7–9 years of hands-on experience in AWS Cloud architecture and operations.

Strong expertise in SageMaker Studio and AWS Bedrock for ML and GenAI enablement.

Proficiency in container orchestration using EKS, ECS (Fargate), and Docker.

Experience with serverless computing using AWS Lambda.

Solid understanding of EC2, IAM, VPC, CloudWatch, and other core AWS services.

Familiarity with Databricks and Snowflake for data engineering and analytics.

CI / CD experience using Jenkins and Infrastructure as Code (IaC) with Terraform.

Strong programming skills in Python.

Excellent problem-solving, communication, and collaboration skills.

Preferred Qualifications :

AWS Certified Solutions Architect / DevOps Engineer / Machine Learning Specialty.

Experience with MLOps and GenAI lifecycle management.

Exposure to multi-cloud environments or hybrid cloud setups.