ML Ops Engineer
Core
Build and scale the infrastructure powering machine learning across the business, enabling innovation, personalization, and data-driven decision-making.
Role type
MLOps Engineer
Builds
Scalable ML platforms, CI/CD pipelines for model deployment, and infrastructure for model training and serving.
Domain
E-commerce / Online Gifting / Cloud Infrastructure
Deliverable
production ML models
Required skills
Python, AWS SageMaker, Terraform, CI/CD pipeline design, model monitoring, infrastructure-as-code, distributed processing, GPU acceleration
Preferred skills
FastAPI, Metaplane, Grafana, SQL, Snowflake, API Gateway, ECS, Lambda, Glue, S3, GitHub Workflows
Technologies
Snowflake, SQL, Python, FastAPI, Metaplane, Grafana, GitHub Workflows, AWS (SageMaker, ECS, Lambda, Glue, S3), Terraform, API Gateway
Responsibilities
Evaluate and implement MLOps tools; design and manage CI/CD pipelines for ML models; build and maintain cloud-native infrastructure for data pipelines and model serving; optimize workflows for performance and scalability; implement monitoring for model performance and automated retraining; develop automated testing and validation workflows; partner with data scientists and engineers to streamline experimentation to production; ensure security best practices; contribute to data platform evolution.
Seniority
Mid-to-Senior, hands-on IC