Fetch 📦
Solve Package Management Permanently
Staff Machine Learning Engineer
Machine Learning EngineerMachine Learning EngineerFull TimeRemoteTeam 201-500Since 2016Company SiteLinkedIn
Location
United States
Posted
7 days ago
Salary
Not specified
No structured requirement data.
Job Description
What we’re building and why we’re building it
Every month, millions of people use America’s Rewards App, 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 SoftBank, 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.
About the Role
Fetch is building the future of personalized consumer experiences. We’re looking for a Staff Machine Learning Engineer to serve as the technical lead for a high-impact ML team focused on personalization, relevance, and ranking.
In this role, you will own the technical direction and execution for your team’s ML systems - driving high-quality architecture, guiding implementation, and ensuring models and infrastructure operate reliably at scale. You’ll partner closely with product and cross-functional stakeholders while remaining deeply hands-on in design and development.
Role Responsibilities
- Serve as the technical lead for a single ML-focused team, setting direction and raising the bar on engineering quality and system design.
- Design, build, and scale ML systems supporting personalization, ranking, search, or ad-related use cases.
- Own end-to-end architecture for your team’s services, including model training, evaluation, deployment, and serving.
- Drive clarity in ambiguous problem spaces, translating product needs into scalable technical solutions.
- Lead design reviews and ensure thoughtful tradeoffs around latency, reliability, experimentation, and maintainability.
- Partner closely with product, data, and engineering stakeholders to deliver measurable business impact.
- Mentor engineers through hands-on technical guidance, feedback, and example.
- Use AI tools to accelerate development and improve system design, including:
- Prototyping and validating ideas with LLM tools.
- Leveraging AI for code iteration and experimentation.
- Using AI assistants for architecture diagramming and design validation.
- Exploring LLM-powered features where appropriate.
Minimum Requirements
- 8+ years of industry experience in machine learning or software engineering, with demonstrated ownership of production ML systems operating at scale.
- Proven experience building and scaling ML systems in personalization, relevance, search, or ad tech domains.
- Strong hands-on expertise in distributed systems, data pipelines, and ML infrastructure.
- Experience deploying ML models into production and operating them at consumer scale.
- Demonstrated ownership of complex technical initiatives within a team.
- Strong systems design skills with the ability to clearly articulate tradeoffs and implementation decisions.
- Experience mentoring engineers and influencing technical standards within a team.
- Ability to operate effectively in ambiguous environments and drive projects to completion.
Preferred Requirements
- Familiarity with LLMs and their application in personalization, feature generation, or search.
- Experience with real-time or streaming ML systems.
- Exposure to experimentation frameworks (A/B testing) and model performance measurement.
- Experience bridging model development with real-time serving systems.
This is a full-time role that can be held from one of our US offices or remotely in the United States.
Compensation: At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. Discover our benefits and how our employees live rewarded at https://fetch.com/careers.
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