Description

You will lead the DevOps and MLOps engineering team, owning the release pipeline and infrastructure for machine learning workloads.

This role is on-site.

Responsibilities

• Manage and scale MLOps teams with 3+ years of leadership experience.
• Deploy and maintain cloud infrastructure on GCP, ensuring containerization with Docker and Kubernetes.
• Implement task orchestration and model tracking using MLflow, Kubeflow, Airflow, Vertex AI, or Azure ML.
• Automate CI/CD pipelines using GitLab CI/CD, GitHub Actions, Jenkins, or GCP Cloud Build.
• Troubleshoot Linux/Unix environments and manage dependency resolution and build processes.

Required Skills

• 5+ years of experience in DevOps, MLOps, or related engineering roles.
• Strong proficiency in Python for scripting and automation.
• Hands-on experience with GCP, Docker, and Kubernetes.
• Familiarity with edge computing architectures.
• Expertise in version control (Git) and dependency management.
• Experience with testing, automation, and build tools like Bazel.
• Understanding of data engineering concepts including Spark, SQL, and Kafka.

Preferred Skills

• Data engineering proficiency with Beam, Pandas, or GCP Dataflow.
• Experience with Azure ML or Vertex AI.

Key Skills

Education

Any Graduate