What you'll do:

• Model Deployment Leadership: Lead the deployment of advanced machine learning models into production environments, ensuring their robustness and scalability.
• Efficient Data Pipelines: Design and optimize data pipelines for efficient and seamless model deployment, leveraging best practices in MLOps.
• Cross-functional Collaboration: Collaborate closely with cross-functional teams, including data scientists, engineers, and business stakeholders, to understand deployment requirements and translate them into actionable strategies.
• MLOps Best Practices: Spearhead the adoption of cutting-edge MLOps methodologies and best practices to streamline deployment processes and enhance model monitoring and management.
• Version Control and Model Tracking: Implement effective version control and model tracking to maintain a reliable model deployment pipeline.
• Performance Monitoring: Monitor deployed models for performance and make necessary improvements or updates as required.
• Compliance and Security: Ensure compliance with data privacy and security regulations throughout the deployment process.
• Issue Resolution: Provide technical leadership in troubleshooting and resolving production deployment issues promptly.
• Documentation and Guidelines: Document deployment processes and create guidelines for team members to follow best practices.
• Continuous Learning: Stay updated with the latest advancements in MLOps and machine learning deployment techniques to continuously improve deployment practices.

What you'll bring:

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field..
• At least 8 years of experience in deploying machine learning models into production with expertise in MLOps tools and methodologies.
• Strong programming skills in Python and relevant MLOps libraries/frameworks.
• Familiarity with tools like Docker, Kubernetes, TensorFlow Serving, or similar for model deployment.
• Understanding of data engineering and pipeline optimization.
• Excellent teamwork and communication skills for cross-functional collaboration.
• Strong analytical and problem-solving abilities.
• Commitment to staying updated with MLOps trends.
• Knowledge of data privacy regulations.
• Leadership experience in deploying machine learning solutions.
• Focus on delivering scalable ML solutions for business growth.