MLOps Engineer – AWS-Focused ML Infrastructure 4

KEYSIGHT TECHNOLOGIES SINGAPORE (SALES) PTE. LTD.

Yishun, Singapore
Not specified
Aws sagemaker and bedrock expertise
Terraform or cloudformation iac
Python scripting and boto3
Keysight Technologies is seeking an MLOps Engineer with a focus on AWS ML infrastructure to enhance operational capabilities for machine learning solutions in manufacturing and semiconductor analytics. The ideal candidate should have 3-5 years of experience in MLOps or cloud engineering, with strong expertise in AWS services and a passion for deploying robust ML systems

Job Summary

  • This role serves as a critical bridge between Machine Learning Engineers and production environments to ensure seamless, reliable, and efficient ML workflows.
  • You will leverage best-in-class AWS tools to enable rapid iteration while maintaining compliance, security, and cost efficiency in regulated industrial settings.
  • The position offers the opportunity to build resilient systems that directly impact innovation and customer outcomes in mission-critical industries like manufacturing and semiconductors.

Matching Summary

Match Score: 85

Keysight Technologies is seeking an MLOps Engineer with a focus on AWS ML infrastructure to enhance operational capabilities for machine learning solutions in manufacturing and semiconductor analytics. The ideal candidate should have 3-5 years of experience in MLOps or cloud engineering, with strong expertise in AWS services and a passion for deploying robust ML systems.

Skills & Requirements

Must-have

  • AWS SageMaker and Bedrock expertise
  • Terraform or CloudFormation IaC
  • Python scripting and Boto3
  • ECR container management
  • CI/CD pipeline automation
  • CloudWatch and X-Ray monitoring

Nice-to-have

  • Manufacturing or semiconductor domain knowledge
  • AWS Certified Machine Learning Specialty
  • Experience with hybrid ML setups
  • SOC 2 or ISO 27001 compliance familiarity
  • Agile methodology participation

Key Requirements

  • Bachelor's or Master's degree in Computer Science or Engineering
  • 3–5 years of experience in MLOps or DevOps roles
  • Deep expertise in AWS services for ML and data workflows

Work Rights

Not specified

Tailored Resume

Cover Letter