MLOps Engineer

Overview

On Site

Depends on Experience

Contract - W2

Contract - Independent

Contract - 12 Month(s)

Skills

("MLOps Engineer" OR "Machine Learning Engineer") AND (AWS OR "Amazon Web Services") AND (SageMaker OR "AWS SageMaker") AND (Docker AND Kubernetes) AND (Glue OR "Step Functions") AND (LLM OR "Large Language Models" OR GenAI OR "Generative AI") AND (Python) AND (Terraform OR CloudFormation)

Job Details

Job Title: MLOps Engineer

Location: South San Francisco, CA (Hybrid 3 days onsite/week)
Type: Contract

Job Description:

We are looking for an experienced MLOps Engineer to support the development, deployment, and monitoring of machine learning models in a production environment. The ideal candidate will have strong experience with AWS services, ML pipelines, GenAI/LLM, and infrastructure automation.

Key Responsibilities:

Build, deploy, and manage ML models using AWS SageMaker, EC2, Lambda, and S3
Design ML pipelines with AWS Glue and Step Functions
Work with LLMs and Amazon Bedrock for GenAI applications
Containerize models using Docker, deploy with Kubernetes (EKS/ECS)
Automate infrastructure with Terraform or CloudFormation
Implement monitoring and alerts using AWS CloudWatch
Integrate ML systems with platforms like Veeva Promomat
Ensure security, reliability, and compliance of ML systems

Required Skills:

Strong experience with AWS tools: SageMaker, Lambda, EC2, S3, Glue, Step Functions, Bedrock
Hands-on experience with LLMs, prompt engineering, and GenAI
Experience with Docker, Kubernetes, Terraform/CloudFormation
Strong Python skills for scripting and automation
Experience with CI/CD and testing in ML pipelines
Familiar with CloudWatch, Textract, and external integrations

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.