Senior Machine Learning Engineer

What we’re building and why we’re building it.

Every month, millions of people use Fetch, earning rewards for buying brands they love, and a whole lot more. Whether shopping in the grocery aisle, grabbing a bite at the drive-through or playing a favorite mobile game, Fetch empowers consumers to live rewarded throughout their day. To date, we’ve delivered more than $1 billion in rewards and earned more than 5 million five-star reviews from happy users.

It’s not just our users who believe in Fetch: with investments from Soft Bank, Univision, and Hamilton Lane, 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.

AI & Data at Fetch sit at the center of how we understand our business, make decisions, and build intelligent products. The organization operates as an integrated AI & data ecosystem, spanning multiple disciplines, including data engineering, analytics engineering, machine learning, experimentation, and data platforms, all working together to turn data into durable business and customer impact. Teams operate in complex problem spaces where requirements evolve, tradeoffs are constant, and the right answer is rarely obvious.

Success depends on strong technical judgment, comfort with ambiguity, and the ability to gather context and make informed decisions while balancing quality, performance, scalability, and responsible use. Practitioners across this org contribute hands-on to production systems, analytical foundations, and intelligent features. You will collaborate closely with product, platform, and engineering partners, help shape standards and best practices, and ensure our AI and data capabilities scale reliably as Fetch grows.

We are seeking a Senior Machine Learning Software Engineer to join Fetch’s Ad Ranking team. This role sits at the intersection of applied machine learning, data engineering, and production systems, with a focus on building and improving ranking, relevance, and optimization models that drive ad selection and delivery  will partner closely with product, data, and platform teams to develop ML-driven decisioning systems, including feature pipelines, model training and evaluation workflows, and low-latency serving infrastructure.

This is a high-impact opportunity to influence how ads are ranked and personalized across the Fetch experience, improving advertiser performance, user engagement, and overall marketplace efficiency.

• Design, build, and improve machine learning models that power ad ranking, relevance, and optimization across the Fetch platform.
• Implement and iterate on active learning strategies, including data sampling, error-driven retraining, and human-in-the-loop workflows to improve ranking quality.
• Leverage LLMs to reduce model development and annotation effort, including synthetic data generation, assisted labeling, weak supervision, and error analysis for ranking and relevance tasks.
• Own ML experimentation, offline and online evaluation, and production inference for assigned ad ranking components.
• Partner closely with product, data, and platform teams to translate advertiser and user experience gaps into measurable ML improvements.
• Maintain high standards for model…