Machine Learning Manager

Deploy•Seattle, WA

About The Position

Deploy is hiring a Machine Learning Manager to lead and grow its machine learning team. The manager will help engineers reach their potential, contribute innovative modeling ideas, and guide machine learning projects involving large-scale datasets and models. The role spans the full model development lifecycle, from data collection and labeling through experimentation, training, testing, and production deployment. It also involves setting team roadmaps and goals, mentoring engineers, coordinating with cross-functional partners, and driving product milestones while maintaining model quality and information security.

Requirements

Undergraduate or graduate degree in computer science or a similar technical field.
At least 4 years of experience as a machine learning engineer, including experience training large deep learning models and working with real-world data.
Knowledge of at least one machine learning focus area, such as computer vision, audio, or NLP.
At least 2 years of experience managing machine learning teams.
Ability to understand and make well-reasoned tradeoffs when designing features.
Ability to set roadmaps and goals for a team and individual members, delegate, mentor, and deliver results.
Willingness to interview engineers, collaborate with a recruiting team, and support smooth onboarding of new team members.
Experience collaborating with product managers and labeling teams to deliver model improvements.

Responsibilities

Work closely with product management, engineering, DevOps, labeling, and sales teams to build a roadmap that supports the team's long-term vision.
Lead and mentor a team of machine learning engineers, helping them achieve their goals.
Participate in product technical design and architecture.
Participate in the full development cycle, including data collection, labeling, model development, experimentation, training, testing, and production deployment.
Drive delivery of product milestones by releasing models with well-tested features and ensuring quality metrics are achieved.
Implement and manage security protocols, including training, code review, and best practices.
Own and manage the risk and security of the business function in coordination with the Security Team.
Maintain awareness of industry best practices for data maintenance and handling as they relate to the role.
Adhere to policies, guidelines, and procedures for protecting information assets.
Report actual or suspected security or policy violations and breaches to an appropriate authority.