MLOps Engineer
About The Role The role sits at the intersection of machine learning and infrastructure: making sure models that data scientists build actually ship, scale, and stay healthy in production. You will build and own CI/CD pipelines, serving infrastructure, and observability systems for ML workloads — the backbone that turns experiments into reliable, monitored products.
Key Responsibilities
Design and maintain end-to-end ML pipelines (training, validation, deployment) using tools like Kubeflow, MLflow, Airflow, or Vertex AI Pipelines Build CI/CD workflows for model and code releases using GitHub Actions, GitLab CI, or Jenkins, with automated testing and staged rollout strategies Deploy and scale model serving infrastructure using Kubernetes, Docker, and frameworks like KServe, Seldon, or Triton Inference Server Implement model monitoring for data drift, latency, and performance regression using tools like Evidently, Prometheus, and Grafana, with automated alerting and rollback triggers Manage feature stores and data versioning systems (Feast, DVC, Delta Lake) to ensure consistency between training and serving environments Optimize infrastructure costs and GPU utilization across training and inference workloads Partner with data scientists and ML engineers to productionize new models, providing clear feedback loops on what breaks and why What We Are Looking For 3–7 years of experience in DevOps, platform engineering, or MLOps, with at least 2 years supporting ML systems in production Strong hands-on experience with Kubernetes and Docker, including deploying stateful and GPU-backed workloads Proficiency in Python and Bash; ability to build tooling and automate operational workflows, not just maintain them Experience with at least one major cloud platform (AWS, GCP, or Azure) and its ML/managed services Working knowledge of ML fundamentals — enough to reason about model versioning, evaluation, and drift without needing a data scientist translate Bachelor's degree in Computer Science, Engineering, or equivalent practical experience