Description

You will build and maintain machine learning pipelines, automate model lifecycle management, and ensure reliable deployment in cloud environments.

This role is remote.

Responsibilities

• Develop and maintain ML pipelines using MLflow, Kubeflow, or Vertex AI.
• Automate model training, testing, deployment, and monitoring across GCP, AWS, or Azure.
• Implement CI/CD workflows for versioning, monitoring, and retraining models.
• Monitor model performance using observability tools and ensure compliance with governance frameworks.
• Provision containerized environments and support low-latency model scoring APIs.

Required Skills

• 10+ years of professional software engineering experience.
• 3+ years of experience in AI/ML and Model Operations.
• Strong proficiency in Java and Python.
• Experience with SQL and ML libraries (scikit-learn, XGBoost, TensorFlow, PyTorch).
• Hands-on experience with cloud platforms and containerization (Docker, Kubernetes).
• Familiarity with data engineering tools (Airflow, Spark) and MLOps frameworks.
• Solid understanding of DevOps practices and software engineering principles.

Preferred Skills

• Experience leveraging AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for rapid deployment.
• Ability to document and explain complex technical concepts to non-technical stakeholders.

Key Skills

Education

Any Graduate