MLOps Engineer: Scale ML Deployments & LLMs

Capgemini; Dallas (TX); On-site; USD 70,000 - 85,000; Full time

Benefits offered by this job

Paid time off

Medical, dental, and vision

Retirement savings plans

Life and disability insurance

Employee assistance programs

Job summary

Capgemini is seeking a skilled ML/AI engineer to deploy models into production and scale with robust MLOps practices. The role emphasizes building reusable AI solutions, leveraging AWS and cloud-native services, and driving end-to-end model lifecycle management in a collaborative environment.

Based in Westlake, TX, this on-site position requires deep know-how in ML infrastructure, LLMs, and scalable architectures.

Qualifications

• 3+ years of experience putting Machine Learning models into production.
• Experience using Mlflow or similar tools for lifecycle management of ML models.
• Docker: experience in creating reproducible and scalable environments for ML deployments.

Skills

AWS

Distributed apps

Systems thinking

ML infrastructure

Pipelines

Python

Typescript

Transformers

PyTorch

Jenkins

Git

Docker

vLLM

LangGraph

Tools

Mlflow

Docker

Jenkins

Git

LangGraph

vLLM

Job description

Capgemini is seeking a skilled ML/AI engineer to deploy models into production and scale with robust MLOps practices. The role emphasizes building reusable AI solutions, leveraging AWS and cloud-native services, and driving end-to-end model lifecycle management in a collaborative environment.

Based in Westlake, TX, this on-site position requires deep know-how in ML infrastructure, LLMs, and scalable architectures.