Description

Own the full lifecycle of machine learning solutions, from pipeline development to deployment and monitoring.

This role is on-site.

Responsibilities

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

Required Skills

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

Key Skills

Education

Any Graduate