Principal Scientist – Machine Learning Engineer

🔥 41 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

🧬 Research Scientist

👻 Ghost score 15%

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Fetch

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2013

👥 B2C

📣 Marketing

🔥 Funding within the last year

💰 Later Stage VC on 2026-05

B2C • Marketing

Fetch is a consumer mobile rewards app that lets users scan receipts to earn points that can be redeemed for gift cards and other rewards. The app awards points for everyday purchases (groceries, fuel, meals, games, etc. ), offers in-app games and promotions, and provides a business-facing offering (Fetch for Business) and browser extension. Fetch reports millions of monthly earners, millions of app reviews, and over $1B in rewards redeemed. The service emphasizes easy receipt scanning, point accumulation, and low-effort rewards for shoppers.

📋 Description

• Design and evolve ML infrastructure supporting personalization, search, ranking, and ad tech. • Build real-time learning systems and data pipelines. • Define architectural patterns for feature infrastructure, model serving, and low-latency, high-throughput decision-making. • Advance data infrastructure, distributed systems, and large-scale data pipelines. • Drive technical design, architecture, and cross-team alignment for major ML initiatives. • Partner with Product, Data Science, Platform, and Engineering teams to build systems adapting to evolving user preferences. • Improve streaming and real-time learning infrastructure for faster iteration across ranking, personalization, and search. • Use AI tools including ChatGPT and Claude for feature design, code generation, prototyping, architecture diagramming, and design validation. • Explore LLMs for personalization, conversational search, and feature creation. • Coach senior engineers and rising technical leads. • Operate effectively amid ambiguity and shape zero-to-one system design practices.

🎯 Requirements

• Proven experience building and scaling ML infrastructure supporting 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 and experience 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 with high levels of ambiguity with minimal direction, prioritize effectively, and drive impact. • 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.

🏖️ Benefits

• Equity: We offer full-time employees equity in Fetch, so that everyone can benefit from Fetch’s growth. • 401(k): Fetch will match your contributions dollar for dollar, up to 4% of your eligible pay. • 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. • Paid Time Off: Flexible PTO, 9 paid holidays, and a year-end week-long break. • Robust Leave Policies: 14 weeks of fully paid parental leave for all employees, plus 6 additional weeks of paid childbirth recovery leave for birthing parents, and a flexible return-to-work schedule. • Calvin Care Cash: One-time $2,000 incentive for employees welcoming new family members. • Flexible Work Environment: Fully remote work from anywhere in the US for US-based roles. • Hardware and software equipment provided for working from home.

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