We’re in search of a dynamic and seasoned MLOps Team Lead.

As a crucial member, you’ll oversee all facets of the Machine Learning lifecycle, including offline and online feature serving for AI models, data pipeline development, model training, CI/CD implementation, and beyond. In this leadership role, you’ll collaborate closely with cross-functional teams to streamline our machine learning processes and contribute to enhancing our MLOps operations. Additionally, you’ll foster personal growth within the team through mentorship, driving our roadmap, technical initiatives, and vision forward.

Responsibilities:

• Data Pipeline for ML: Conceptualize, design, and implement scalable and robust systems for feature engineering, catering to both online and offline inference workflows.
• Model Deployment: Lead the development and implementation of scalable systems for deploying machine learning models into production environments.
• CI/CD Implementation: Establish and manage CI/CD pipelines to ensure seamless updates and releases of our machine learning models.
• Monitoring and Quality: Implement robust monitoring and logging mechanisms to detect anomalies and drifts in AI components, ensuring high-quality performance.
• Collaboration: Work closely with DevOps and Data science teams to seamlessly integrate machine learning solutions into existing infrastructure

Qualifications:

• Leadership Experience: Minimum of 3 years of proven experience in a team leadership role.
• Machine Learning Expertise: Over 5 years of demonstrated experience as a Machine Learning Engineer, specializing in model deployment and feature pipeline development.
• Strong Programming Skills: Proficiency in Python, Java, or Scala.
• Technical Proficiency: Experience with containerization technologies (e.g., Docker, Kubernetes) and cloud platforms (AWS, Azure, GCP).
• MLOps Tools: Familiarity with MLOps tools and frameworks such as MLflow, Kubeflow, and Sagemaker.
• CI/CD Practices: Understanding of continuous integration and continuous deployment practices.
• Communication Skills: Excellent communication abilities to effectively collaborate with cross-functional teams.
• Education: Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field.