AI/ML Platform Engineer job

The AI/ML Platform Engineer will develop, maintain, and optimize infrastructure, tools, and automated workflows supporting the shared enterprise AI/ML platform. The role focuses on ML pipeline automation, CI/CD, model deployment, monitoring, cloud cost optimization, and developer enablement.

• 5+ years of experience in software engineering, data engineering, or ML engineering, including 2+ years working with production ML systems.
• Bachelor’s degree in Computer Science, Engineering, or a related technical field master’s degree or PhD preferred.
• Strong proficiency in Python and production-quality code development.
• Understanding of ML and deep learning fundamentals, including model training, evaluation, feature engineering, versioning, and deployment.
• Experience with PyTorch, TensorFlow, or scikit-learn.
• Experience with Apache Airflow, Kubeflow Pipelines, Prefect, or equivalent orchestration tools.
• Familiarity with AWS, Azure, or GCP and managed AI/ML services.
• Experience with Docker, basic Kubernetes operations, and CI/CD tools such as GitHub Actions, GitLab CI, or Jenkins.
• Experience building, deploying, monitoring, and troubleshooting ML pipelines and production workflows.
• Experience monitoring model performance, data drift, pipeline health, and infrastructure utilization.
• Strong analytical, debugging, communication, and collaboration skills.

Preferred Experience:

• Prometheus, Grafana, or Datadog.
• MLflow or Weights & Biases.
• Terraform or Ansible.
• Feature stores such as Feast or Tecton.
• Internal developer tools, SDKs, and self-service platform capabilities.
• NLP, computer vision, speech processing, reinforcement learning, or Generative AI.
• Government, regulated, or large enterprise environments.