ML Engineering Manager

Job Responsibilities

• Build and lead an ML engineering team from hiring through onboarding, career development, and performance management
• Own the technical strategy and roadmap for ML systems—from model development through deployment, monitoring, and retraining pipelines
• Partner with product, data, and platform teams to translate business requirements into ML solutions and define success metrics
• Drive code quality, testing rigor, and production best practices across the team; establish standards for model governance and experimentation
• Identify and remove technical and organizational blockers; advocate for team resources and tooling investments
• Mentor engineers on ML fundamentals, system design, and career growth; create space for learning and exploration
• Stay current with ML tooling, architecture patterns, and infrastructure trends; evaluate and integrate new technologies thoughtfully

Candidate Requirements

• 7+ years of hands-on ML or AI/ML engineering experience, including production model development, deployment, and monitoring
• 3+ years managing or leading ML engineers; demonstrated ability to hire, mentor, and retain strong technical talent
• Fluency in the full ML lifecycle: data preparation, feature engineering, model training, evaluation, deployment, and operational maintenance
• Strong systems thinking—you design for scalability, reliability, and observability, not just model performance
• Comfortable working in-person in Boston; ability to build team culture and psychological safety through presence and direct collaboration
• Track record of shipping ML systems that drive measurable business value, not proof-of-concepts