Senior Manager, Machine Learning Engineering

Role Responsibilities

• Lead and develop a team of machine learning engineers responsible for business-critical Ad Platform systems.
• Translate product and technical strategy into quarterly and annual roadmaps with measurable product, technical, and delivery outcomes.
• Guide the development of ML solutions for areas such as ad ranking, targeting, bidding, inventory forecasting, optimization, and measurement.
• Partner with Product, Data Science, Analytics, and Engineering teams to define success metrics, experimentation strategies, and technical priorities.
• Make sound trade-offs across delivery speed, model performance, scalability, reliability, maintainability, and technical debt.
• Raise the engineering bar through strong design reviews, code reviews, operational ownership, and architectural standards.
• Proactively identify technical and organizational risks before they constrain delivery or platform growth.
• Coach engineers on system design, technical decision-making, execution, and career development.
• Use data, experiments, incidents, system performance, and delivery metrics to guide priorities and improve team effectiveness.
• Drive alignment and execution across teams with shared systems, goals, and dependencies.

Minimum Requirements

• 8+ years of experience in software engineering, machine learning engineering, or a related technical field, including 2+ years managing and developing engineering teams.
• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience.
• Experience managing and developing machine learning or software engineers in a product-focused environment.
• Strong technical background building and operating production machine learning systems at scale.
• Experience translating business and product objectives into technical roadmaps and measurable outcomes.
• Strong understanding of the ML lifecycle, including data quality, feature development, training, evaluation, deployment, monitoring, and iteration.
• Experience making technical trade-offs involving model quality, latency, scalability, reliability, and maintainability.
• Ability to lead teams through medium-to-high ambiguity and complex cross-functional dependencies.
• Demonstrated experience coaching senior engineers and raising technical and operational standards.
• Strong communication and stakeholder-management skills, including the ability to influence without direct authority.
• Proficiency with Python and SQL and experience with modern machine learning frameworks and cloud-based data or ML systems.
• Experience establishing accountability for both delivery outcomes and the long-term technical health of owned systems.

Preferred Requirements

• Master’s degree or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Engineering, or a related technical field.
• Experience building machine learning systems for advertising, recommendations, ranking, personalization, or marketplace optimization.
• Familiarity with ad auction dynamics, bidding, targeting, inventory forecasting, attribution, and campaign measurement.
• Experience leading teams responsible for low-latency, high-scale production systems.
• Strong understanding of experimentation, causal inference, and incrementality measurement.
• Experience with modern MLOps practices, feature platforms, model monitoring, and automated training and deployment pipelines.
• Experience working with large-scale data processing and distributed systems.
• Demonstrated success leading cross-team technical initiatives in a rapidly evolving product environment.

Compensation & Benefits

• Competitive compensation packages including base, equity, and benefits.
• Equity in Fetch.
• 401k Match: Dollar-for-dollar match up to 4%.
• Comprehensive medical, dental and vision plans for everyone including your pets.
• $10,000 per year in education reimbursement.
• Employee Resource Groups focused on diversity and inclusion.
• Paid Time Off.