Senior Manager, Machine Learning Engineering - Ad Platform

Fetch helps people live rewarded every day, with a vision to become the rewards destination for everyone. We turn everyday activities into meaningful rewards, whether it’s grocery shopping, grabbing a quick meal, or playing a favorite mobile game. To date, we’ve awarded more than $1 billion in Fetch Points to our users. Each day, more than 13 million receipts are submitted on Fetch, providing visibility into over $212 billion in gross merchandise value. This creates the largest retail-agnostic, SKU-level view of household spending, powering Fetch as an outcomes-based advertising platform that helps brands acquire and retain lifelong consumers.

The Fetch app is available on the App Store and Google Play, with more than 6 million five-star reviews from a highly engaged and loyal user base. It’s not just our users who believe in Fetch: with investments from Softbank, ICONIQ, DST, Greycroft, and partnerships ranging from challenger brands to Fortune 500 companies, Fetch is reshaping how brands and consumers connect in the marketplace.

When you work at Fetch, you play a vital role in a platform that drives brand loyalty and creates lifelong consumers with the power of Fetch points. User and partner success are at the heart of everything we do, and we extend that same commitment to our employees. At Fetch, we value curiosity, adaptability, and the confidence to explore new tools, especially AI, to drive smarter, faster work. You don’t need to be an expert, but you should be ready to learn quickly and think critically. We welcome learners who move fast, challenge the status quo, and shape what’s next, with us.

Ranked as one of America’s Best Startup Employers by Forbes for two years in a row, Fetch fosters a people-first culture rooted in trust, accountability, and innovation. We encourage our employees to challenge ideas, think bigger, and always bring the fun to Fetch.

About Engineering at Fetch

At Fetch, engineering is driven by curiosity, ownership, and a bias toward action. We operate in complex problem spaces where the right answer is not always clear, and success depends on adaptability, critical thinking, and informed decision-making. Our engineers are comfortable navigating ambiguity, understanding tradeoffs, gathering context, and turning uncertainty into progress while maintaining high technical standards. Engineers at Fetch take pride in building reliable, scalable systems that serve millions of users. You will contribute directly to the codebase, collaborate closely with cross-functional partners, and help shape best practices that elevate the quality of our work. We foster a culture of mentorship and collaboration, where engineers grow by learning from one another and holding a high bar for quality, reliability, and impact.

About The Role

Fetch is looking for a Senior Manager of Machine Learning Engineering to lead the team building and scaling machine learning capabilities across our Ad Platform. You will partner with Product, Data Science, Engineering, and business stakeholders to translate strategy into a measurable roadmap that improves advertiser outcomes, member experience, and marketplace performance. You will lead engineers through ambiguous, business-critical problems while maintaining a strong balance between product delivery, model quality, reliability, scalability, and long-term technical health.

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.

Requirements

• 6+ 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 Qualifications

• 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.

Benefits

• Equity: Full-time employees receive equity in Fetch, so everyone can benefit from Fetch’s growth.
• 401k Match: Dollar-for-dollar match up to 4%.
• Health Benefits: Comprehensive medical, dental, and vision plans for employees and their pets.
• Continuing Education: $10,000 per year in education reimbursement.
• Employee Resource Groups: Participate in employee-led groups centered around fostering a diverse and inclusive workplace through events, dialogue, and advocacy.
• Paid Time Off: Flexible PTO, 9 paid holidays, and a year-end week-long break.
• Robust Leave Policies: 20 weeks of paid parental leave for primary caregivers, 14 weeks for secondary caregivers, and a flexible return-to-work schedule.
• Calvin Care Cash: A one-time $2,000 incentive to assist employees welcoming new family members with childcare, clothing, diapers, and more.
• Flexible Work Environment: Work from one of our stunning offices or fully remotely from anywhere in the U.S., with hardware and software provided.

This is a full-time role that can be held from one of our US offices or remotely in the United States.