Description

You will lead the design, development, and deployment of ML Ops infrastructure supporting AI and ML initiatives.

This role is remote.

Responsibilities

• Build and maintain scalable data pipelines and automated systems for model training, testing, and deployment.
• Develop and implement best practices for monitoring, versioning, and maintaining ML models in production.
• Collaborate with cross-functional teams to deliver secure and efficient AI solutions.
• Drive adoption of AI and GenAI capabilities across the product portfolio.
• Mentor team members in AI/ML engineering practices.

Required Skills

• Strong experience in ML Ops, including designing and deploying end-to-end machine learning pipelines.
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience with cloud platforms (AWS, Azure, or GCP) and containerization (Docker).
• Solid understanding of CI/CD for ML systems and model monitoring.
• Demonstrated ability to apply data-driven insights to drive innovation.
• Experience working in an agile environment.
• Bachelor's degree in Computer Science, Engineering, or related field.

Key Skills

Education

Bachelor's degree