MLOps Engineer

Role: MLOps Engineer
Location:   Bay Area, CA (Hybrid)-only PST candidates
Experience: 12+ years
Visa: Independent only

This role focuses on driving the full lifecycle of machine learning solutions, including building and maintaining ML pipelines, automating model deployment, and working with cutting-edge cloud and MLOps technologies.

Key Highlights of the Role:
* Develop and manage ML pipelines using tools like MLflow, Kubeflow, or Vertex AI
* Implement CI/CD workflows for model lifecycle (training, deployment, monitoring)
* Work across cloud platforms such as AWS, GCP, or Azure
* Collaborate on containerized environments using Docker & Kubernetes
* Leverage AutoML tools for rapid model development and deployment

What We’re Looking For :
* 10+ years in software engineering with 3+ years in ML/MLOps
* Strong experience with Python/Java, SQL, and ML frameworks (TensorFlow, PyTorch, etc.)
* Hands-on experience with cloud platforms and data engineering tools (Airflow, Spark)
* Solid understanding of DevOps practices and model governance