Senior Manager, Machine Learning Engineering
Lead a team of ML engineers building and scaling production ML systems for Fetch's Ad Platform, including ad ranking, targeting, bidding, and optimization. Requires 8+ years technical experience (2+ managing teams), strong ML lifecycle and production systems expertise, and cross-functional partnership skills.
About the job
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.
Skills
Python, SQL, Machine Learning, MLOps, AWS, Distributed Systems, Experimentation, Causal Inference
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