Minimum Salary: $110,000.00 - $116,750.00

ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, our most valuable asset is our people. Here you'll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers and consumers, worldwide. ZSers drive impact by bringing a client first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning; bold ideas; courage and passion to drive life-changing impact to ZS.

• Collaborate with data science teams to create a streamlined, automated pipeline for transitioning ML models from development to production.

• Design, Develop and maintain processes for model versioning, training, deployment, and continuous updates.

• Implement best practices for model monitoring, performance evaluation, and drift detection.

• Design and build scalable, reproducible infrastructure for ML development and deployment.

• Implement infrastructure as code (IaC) principles to ensure consistent and reliable ML environments.
• Integrate ML pipelines into continuous integration and continuous deployment (CI/CD) workflows.
• Ensure reliable and efficient deployment of ML models into production environments.

• Implement monitoring solutions to track model performance, data quality, and system health.
• Troubleshoot and optimize ML pipelines for improved efficiency, reliability, and scalability.
• Implement robust security controls and access management for ML systems.

• Ensure compliance with industry standards (e.g., GDPR, HIPAA) during model deployment.
• Collaborate with legal and compliance teams to address regulatory requirements.
• Lead and mentor a team of junior MLOps Engineers, fostering their growth and skill development.

• Provide technical guidance on MLOps frameworks, deployment strategies, and observability best practices.
• Cultivate a culture of continuous learning, innovation, and knowledge sharing within the team.
• Work closely with business stakeholders to understand ML project objectives and requirements.

• Communicate effectively with project managers, and cross-functional teams.

• Provide regular updates on project progress, performance, and any issues or risks.

• 3 to 5 years of hands-on experience in cloud engineering, infrastructure, or related roles.

• Minimum of 4 years of professional experience in MLOps, machine learning, and DevOps.

• Bachelor's degree in computer science, Data Science, Information Technology, or a related field.
• Proficiency in Python, SQL, and relevant ML libraries (e.g., TensorFlow, PyTorch).

• Familiarity with cloud platforms (e.g., GCP, AWS) and containerization (Docker, Kubernetes).

• Strong problem-solving skills and ability to work in a collaborative environment.

• Expertise in software development methodologies, such as Agile, DevOps, and CI/CD.

• Proficiency in programming languages, including Python and R.
• Excellent communication and stakeholder management skills.

• Preferred certifications in cloud platforms (e.g., AWS, Azure, GCP) and MLOps.

• Azure synapse experience preferred