Platform Engineer

Actively Reviewing the Applications

CBTS

India Contract On-site

Posted 8 hours ago • Apply by June 4, 2026

Job Description

JOB DESCRIPTION

We are seeking a Platform Engineer to help support and enhance our AWS-based machine learning platform, SageMaker. This role focuses on maintaining and improving infrastructure that enables data scientists and ML engineers to build, train, and deploy models efficiently and securely. This candidate should have foundational cloud and infrastructure-as-code experience, strong troubleshooting skills, and an interest in supporting machine learning workloads.

Key Responsibilities

• Assist in building, maintaining, and improving AWS infrastructure supporting Amazon SageMaker and related ML services.

• Develop and maintain Infrastructure as Code (IaC) using Terraform to provision, manage, and version cloud resources.

• Assist with CI/CD pipeline development and automation for infrastructure and ML workflows.

• Help design, implement and maintain core components and services using best practices for cloud architecture and security.

• Monitor platform reliability, performance, cost efficiency and assist in troubleshooting infrastructure and deployment issues.

• Collaborate with data scientists and ML engineers to understand platform needs to improve stakeholder experience.

• Participate in documentation, operational runbooks, and knowledge sharing.

Required Qualifications

• Understanding of core AWS components and services such as:

- Networking - subnets, routing, DNS, and security groups

- Security - IAM roles/policies, encryption, secrets management, and least-privilege access models

- EC2/ECS

- S3

- Lambda

- SQS

• Experience with:

- Experience developing in Python (Lambda services, scripting, etc.)

- Terraform or other infrastructure-as-code tools

- CI/CD tooling (Jenkins, GitHub Actions, or similar)

• Exposure to Linux-based environments and shell scripting.

• Strong problem-solving skills and willingness to learn new technologies.

• Ability to collaborate effectively with cross-functional teams.

Preferred Qualifications

• Exposure to Amazon SageMaker or other ML platform tooling.

• Basic understanding of machine learning workflows (training, inference, data pipelines, model lifecycle), as well as connectivity and execution patterns (batch, realtime).

• Familiarity with containerization and orchestration technologies such as Docker or Kubernetes.

• Experience developing OIDC-integrated applications