Manager, Machine Learning

Key Responsibilities

• Lead the execution of the RD and product roadmap, leveraging industry insights and business needs to drive ML initiatives while managing team priorities and timelines.
• Collaborate with cross-functional stakeholders to ensure alignment of ML solutions with overarching business objectives, effectively communicating technical concepts to non-technical audiences.
• Oversee the development of robust APIs and microservices, ensuring smooth integration of ML models into production environments, and guide the team in building feature pipelines for model serving.
• Mentor and develop machine learning engineers, fostering a positive and productive work environment through training, guidance, and constructive feedback.
• Conduct code reviews and establish best practices to maintain high quality and performance standards while promoting adherence to version control and model governance.
• Manage and optimize end-to-end MLOps pipelines for data collection, model training, validation, and monitoring, while ensuring team collaboration and effective resource allocation.
• Drive the implementation of model compression, quantization, and distributed training techniques to enhance performance, encouraging innovative solutions from team members.
• Track key metrics and optimize deployed models to ensure ongoing effectiveness, collaborating with team members to identify improvement opportunities.
• Collaborate with cloud architects and DevOps teams to design and maintain scalable ML infrastructure, ensuring effective resource management and deployment.
• Work closely with applied scientists and analysts to transform model requirements into production-ready solutions, facilitating teamwork across departments.
• Establish and maintain monitoring and alerting systems for deployed models, ensuring prompt issue resolution while guiding the team in best practices.
• Create and uphold documentation for ML architecture and best practices to ensure knowledge sharing within the team, promoting continuous improvement.
• Stay current with advancements in ML technologies and lead ongoing enhancement initiatives within the team, encouraging team participation in the ML community.

Required Qualifications

Preferred Qualifications

Skills Required

Machine Learning, Sqs, Kafka, Python