Principal Machine Learning Engineer

AI in this role

chatgptclaude

What we’re building and why we’re building it.
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.
Meet Fetch Engineering
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 entering its AI-first era, and we're looking for a Principal Machine Learning Engineer to design, scale, and evolve the intelligent systems that power personalization, relevance, and ranking across our platform. You will build the ML infrastructure and real-time learning systems that enable Fetch to serve more relevant, adaptive, and high-performing experiences for millions of users.
Operating at the intersection of ML infrastructure, personalization, and large-scale distributed systems, you will be a key technical force shaping how Fetch's ML systems evolve. You'll collaborate with Product, Data Science, Platform, and Engineering teams to drive clarity, define architectural standards, and ensure our ML systems become smarter, faster, and more adaptive to evolving user preferences over time.
This is a hands-on, high-impact technical leadership role with influence across multiple engineering collectives. Your work will shape how Fetch builds and scales ML infrastructure: personalization, search, ranking, real-time learning, and feature systems at consumer scale.
Role Responsibilities
Architect for Scale and Intelligence: Design and evolve the ML infrastructure supporting personalization, search, ranking, and ad tech. Build systems that prioritize relevance, adaptability, and measurable user value.
Advance Intelligence in Production: Design and implement zero-to-one systems, including real-time learning and data pipelines. Define architectural patterns for feature infrastructure, model serving, and low-latency, high-throughput decision-making at consumer scale.
Evolve the ML Platform: Advance the core systems powering personalization and ranking, including data infrastructure, distributed systems, and large-scale data pipelines. Pioneer new approaches that raise both model performance and system efficiency.
Lead Through Influence and Product Partnership: Drive technical design, architecture, and cross-team alignment for major ML initiatives. Partner with product and engineering teams to create dynamic systems that adapt to evolving user preferences, and translate architectural tradeoffs into measurable outcomes.
Scale Experimentation & Learning Systems: Improve streaming and real-time learning infrastructure to enable faster iteration across ranking, personalization, and search systems.
Accelerate Innovation Velocity: Use AI tools to accelerate your work, including designing features and validating ideas with ChatGPT and Claude sandboxes, leveraging AI for code generation and technical prototyping, using AI assistants for systems architecture diagramming and design validation, and exploring LLMs to enhance personalization, conversational search, and feature creation.
Mentor & Multiply Engineering Impact: Coach senior engineers and rising technical leads, elevating standards for architectural clarity, technical execution, and design quality. Help raise the bar across the team and amplify impact through reusable frameworks and technical patterns.
Model Technical Excellence: Operate effectively in high levels of ambiguity with minimal direction, prioritizing effectively and driving impact. Shape the engineering culture around thoughtful, zero-to-one system design.
Minimum Requirements

Proven experience building and scaling ML infrastructure in support of personalization, relevance, search, or ad tech systems.
Deep hands-on expertise in data infrastructure, distributed systems, and large-scale data pipelines for ML systems.
Experience working at a consumer product company with ML models operating at scale.
Prior contributions to ranking, personalization, or ad tech systems with measurable business impact.
Strong systems design skills, with a track record of leading architecture and communicating design tradeoffs.
Experience mentoring and elevating other engineers.
Success leading zero-to-one technical initiatives and delivering new infrastructure or ML systems from scratch.
Ability to operate in high levels of ambiguity with minimal direction, prioritizing effectively and driving impact.

Preferred Requirements

Familiarity with LLMs and their application in personalization, feature creation, and conversational search.
Experience with streaming/real-time learning systems.
Exposure to conversational search or large-scale information retrieval.
Previous work bridging model development with real-time serving systems.

This role can be based in one of our US offices or remotely within 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.
At Fetch, we'll give you the tools to feel healthy, happy and secure through:

Equity: We offer full-time employees equity in Fetch, so that everyone can benefit from Fetch’s growth.
401k Match: Dollar-for-dollar match up to 4%.
Benefits for humans and pets: We offer comprehensive medical, dental and vision plans for everyone including your pets.
Continuing Education: Fetch provides ten thousand per year in education reimbursement.
Employee Resource Groups: Take part in employee-led groups that are centered around fostering a diverse and inclusive workplace through events, dialogue and advocacy. The ERGs participate in our Inclusion Council with members of executive leadership.
Paid Time Off: On top of our flexible PTO, Fetch observes 9 paid holidays, as well as our 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: Employees who are welcoming new family members will also receive a one time $2,000 incentive to assist employees with covering the cost of childcare, clothing, diapers and much more!
Flexible Work Environment: Collaborate with your team in one of our stunning offices, or you can work fully remotely from anywhere in the US. We’ll ensure you are equally equipped with the hardware and software you need to get your job done in the comfort of your home. (applicable for most roles)

Fetch is an equal opportunity employer that embraces diversity, inclusion, and respect for all individuals. We do not discriminate on the basis of race, color, religion, gender, gender identity or expression, sexual orientation, age, national origin, marital status, veteran status, disability, or any other characteristic protected by applicable law. Our commitment to inclusivity ensures that everyone is treated with dignity and has the opportunity to succeed based on their talent, skills, and potential.
Fetch also provides reasonable accommodations to qualified individuals with disabilities or those with sincerely held religious beliefs, as required by law. If you need assistance with the application process or require an accommodation, please contact us at accommodations@fetch.com.

How we score this

Principal Machine Learning Engineer at Fetch scores 94 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

Classification

AI Level 4. Building AI systems is the job itself: without AI, the role would not exist.

AI Level 480 to 100
AI Level 360 to 79
AI Level 240 to 59
AI Level 10 to 39

Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

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A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ChatGPTClaude

Questions you could be asked

What's a project where you used ChatGPT hands-on?
Walk me through how you've used Claude in your day-to-day work.
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: ChatGPT and Claude. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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