FetchPosted 5mo ago

Senior Machine Learning Engineer I

Senior Machine Learning Engineer I at Fetch scores 85 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.

Remote (United States - Remote)seniorfull_time

AI in this role

chatgptcopilotlangchainbedrock

computer-vision

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.
About the Role
We are seeking a Machine Learning Software Engineer to join Fetch’s Scan, Match & Catalog team. This role sits at the intersection of applied machine learning, data engineering, and production systems, with a focus on improving receipt understanding, product matching, and catalog enrichment at scale. You will partner closely with product, operations, and platform teams to deliver ML-driven automation, including computer vision and OCR pipelines, LLM-based workflows, and scalable ML services. This is a high-impact opportunity to help shape Fetch’s Scan-to-Catalog foundation and significantly increase automation, quality, and match coverage across the platform.
This is a full-time role that can be held from one of our US offices or remotely in the United States.
Role Responsibilities

Build and scale ML models across the scan, match, and catalog pipeline, supporting receipt understanding, product matching, and catalog enrichment.
Implement and iterate on active learning strategies, including data sampling, error-driven retraining, and human-in-the-loop workflows.
Leverage LLMs to reduce model training and annotation effort, including synthetic data generation, assisted labeling, weak supervision, and error analysis.
Own ML experimentation, evaluation, and production inference for assigned SMaC components.
Collaborate with product, data, and platform partners to translate quality gaps into ML improvements.
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

4+ years experience in software engineering, with production-level coding experience.
Strong proficiency in Python for ML development, with working knowledge of Go, and hands-on experience deploying models into production systems. Experience with AWS technologies and distributed systems.
Practical experience applying LLMs to reduce training and annotation effort, including assisted labeling, synthetic data generation, weak supervision, or error analysis.
Strong engineering mindset with the ability to deliver reliable, maintainable, and scalable systems.
Experience with AI-assisted coding tools (e.g., GitHub Copilot, ChatGPT, or similar) to improve development efficiency and code quality.
Ability to critically evaluate AI-generated outputs, with strong debugging and problem-solving skills to validate correctness.

Preferred Requirements

Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field. Equivalent practical experience considered in lieu of degree.
Familiarity with AI tools and frameworks like AWS Bedrock, Langchain, vector databases, or similar AI orchestration technologies.
Experience with machine learning workflows and large language models (LLMs).
Familiarity with orchestrating ML-driven actions in high-complexity or high-throughput environments.
Hands-on experience with computer vision and OCR, such as receipt/document parsing, layout-aware modeling, or image-based ML pipelines.

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.

Prepare for this job

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

Computer VisionChatGPTCopilotLangChainBedrock

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
Walk me through how you've used ChatGPT in your day-to-day work.
What are the limits of Copilot that you've run into, and how did you work around them?
What's a project where you used LangChain hands-on?
Walk me through how you've used Bedrock in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Computer Vision, ChatGPT, Copilot, LangChain, and Bedrock. 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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