Senior Machine Learning Engineer
Core
Design, build, and operate MLOps infrastructure to deploy machine learning and large language models safely and at scale.
Role type
Senior MLOps Engineer
Builds
End-to-end MLOps platform, CI/CD pipelines, and scalable model-serving infrastructure
Domain
Cloud Infrastructure (AWS, Databricks) and MLOps
Deliverable
production ML models
Required skills
Cloud engineering, DevOps, MLOps, CI/CD, Model serving, Observability, Security, Infrastructure as Code
Preferred skills
LLM deployment patterns, GPU optimization, Disaster recovery
Technologies
AWS, Databricks, Terraform, AWS CloudFormation, MLflow, Amazon SageMaker, Amazon ECS, Amazon EKS, API Gateway
Responsibilities
Design scalable MLOps platform architectures; Build automated CI/CD pipelines for model artifacts and inference services; Operate secure, low-latency inference endpoints for traditional ML and LLMs; Implement reliability, recovery, and business continuity procedures; Establish end-to-end observability for models and infrastructure; Enforce security controls and governance for model-serving environments; Automate infrastructure provisioning using Infrastructure as Code.
