MLOps Engineer
Core
Build and manage automation pipelines to operationalize ML platform, design model training and deployment infrastructure, and enforce MLOps best practices.
Role type
MLOps Engineer
Builds
ML platform, model training and deployment infrastructure, automation pipelines
Domain
B2B data and sales intelligence, Cloud infrastructure
Deliverable
production ML models
Required skills
AWS cloud architecture, MLOps best practices, Machine Learning fundamentals, Data Engineering fundamentals, Infrastructure as Code (Terraform/CDK), CI/CD pipelines (GitHub Actions/CircleCI), Cloud networking and security, Containerization (Docker/ECS/Kubernetes), Python, Production ML model deployment and monitoring
Preferred skills
MLOps Platforms (SageMaker/VertexAI/Databricks), Scala, ML Frameworks (scikit-learn/Keras/PyTorch/Tensorflow), SQL/NoSQL databases, data lakehouse experience
Responsibilities
Lead MLOps initiatives during platform implementation, Design and implement secure, reliable, scalable AWS architectures, Bridge AI, Engineering, and DevSecOps for ML deployment, Monitor and maintain production critical ML services
Seniority
Mid-level, hands-on IC
