Manager, AI/ML Framework

About Calix

Calix delivers a cutting-edge broadband platform combined with managed services, empowering service providers to enhance the quality of life in communities across the United States. We re leading a transformative era in broadband technology, enabling connectivity and unrivaled digital experiences in underserved regions. Join us as we continue to innovate and help our customers unlock their full potential.

Role Overview

Calix is looking for an accomplished Manager, ML Framework. This role will oversee the engineering team responsible for building robust data pipelines for model training, model serving infrastructure, and end-to-end ML platform capabilities. The ideal candidate brings extensive experience in ML engineering leadership, deep expertise in MLOps tools and workflows, and proven success in building production-grade ML infrastructure.

Key Responsibilities:

Team Leadership:

• Lead and manage a team of ML engineers and MLOps specialists, fostering a culture of collaboration, innovation, and continuous improvement.

• Recruit, mentor, and develop engineering talent with expertise in ML frameworks and operations, ensuring the team is motivated and equipped to achieve objectives.

• Strong leadership and communication skills, with the ability to work across technical and non-technical teams.

Project Management:

• Define project goals, timelines, and deliverables for ML model development and MLOps infrastructure in alignment with business priorities.

• Oversee the entire ML lifecycle, from data pipeline development and model training to deployment, monitoring, and maintenance.

• Document process workflows, technical documentation, and provide training to various stakeholders on ML platform capabilities.

ML Model Development and Operations:

• Oversee the implementation of comprehensive MLOps practices, including model deployment, versioning, monitoring, and lifecycle management.

• Drive the development of critical MLOps components: experiment tracking, feature store, model registry, and data lineage tracking systems.

• Collaborate with data scientists to ensure a seamless transition from experimentation to production, maintaining model performance and reliability.

Data Pipeline Engineering:

• Oversee the design and development of scalable data pipelines for model training, ensuring data quality, reliability, and efficiency.

• Implement best practices for data ingestion, transformation, and feature engineering to support diverse ML workflows.

• Ensure robust data lineage tracking and governance across all pipeline stages.

Technical Oversight:

• Ensure best practices in coding, testing, and system design are followed across ML pipelines and infrastructure.

• Conduct code and architecture reviews to ensure robust, scalable, and maintainable ML systems.

• Maintain hands-on involvement in critical technical decisions and code contributions when needed.

Qualifications

• Bachelors or master s degree in computer science, Software Engineering, Machine Learning, or a related field.

• 8-12 years of experience in software development with a strong focus on ML engineering and data pipelines.

• 3-5 years in a leadership or managerial role, with proven ability to remain hands-on and contribute to code.

• Strong proficiency with ML frameworks like scikit-learn, XGBoost, TensorFlow, or PyTorch.

• Hands-on experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, Airflow, or similar).

• Deep understanding of data pipeline development using tools like Apache Spark, Kafka, or similar technologies.

• Experience with cloud platforms (e.g., Google Cloud) and deploying ML models as services.

• Strong understanding of microservices architecture, containerization (Docker, Kubernetes), and CI/CD pipelines.

• Excellent communication, collaboration, and problem-solving skills.

• Proven ability to balance strategic leadership with hands-on technical contributions.

• India - (Flexible hybrid work model - work from Bangalore office for 20 days in a quarter)