- 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 performance, reliability, latency, and data quality in production ranking systems.
- Use AI-assisted tools to accelerate development, experimentation, debugging, and analysis while maintaining strong engineering judgment.
- Designing features and validating ideas with ChatGPT & Claude sandboxes.
- Leveraging AI for code generation and technical prototyping.
- Using AI assistants for systems architecture diagramming and design validation.
- 6+ years of software engineering experience with a strong track record of building and maintaining production ML or data-driven systems.
- Strong proficiency in Python for machine learning and data processing, with working knowledge of Go, and hands-on experience deploying low-latency models into production ranking or decisioning systems.
- Experience with AWS and distributed systems, including building or operating scalable training pipelines and online inference services.
- Practical experience applying LLMs to reduce model development and data labeling effort, including assisted labeling, synthetic data generation, weak supervision, or model error analysis.
- Strong engineering judgment and systems mindset, with an emphasis on reliability, performance, and long-term maintainability of ranking or optimization systems.
- Experience using AI-assisted development tools (e.g., GitHub Copilot, ChatGPT, or similar) to accelerate iteration while maintaining high code quality.
- Ability to critically evaluate AI-generated outputs, debug complex issues, and validate correctness in production ML workflows.
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
- Familiarity with modern AI tooling and frameworks such as AWS Bedrock, LangChain, vector databases, or similar orchestration technologies used in ML-powered decisioning systems.
- Experience building and operating machine learning workflows involving large language models (LLMs), including prompt-driven systems and model-assisted pipelines.
- Familiarity with orchestrating ML-driven decisions in high-throughput or low-latency environments, such as ranking, recommendation, or optimization systems.
- Experience with applied machine learning for relevance, ranking, or personalization problems (e.g., feature engineering, model evaluation, or feedback loops).
- Experience working in small, fast-moving, cross-functional teams, partnering closely with product, data, and platform stakeholders.
- 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)
Skills Required
- 6+ years of software engineering experience building and maintaining production ML or data-driven systems.
- Strong proficiency in Python for machine learning and data processing.
- Working knowledge of Go.
- Hands-on experience deploying low-latency models into production ranking or decisioning systems.
- Experience with AWS and distributed systems, including building or operating scalable training pipelines and online inference services.
- Practical experience applying LLMs for assisted labeling, synthetic data generation, weak supervision, or model error analysis.
- Strong engineering judgment and systems mindset focused on reliability, performance, and maintainability.
- Experience using AI-assisted development tools (e.g., GitHub Copilot, ChatGPT) to accelerate iteration while maintaining code quality.
- Ability to critically evaluate AI-generated outputs, debug complex issues, and validate correctness in production ML workflows.
- Bachelor's or Master's degree in Computer Science, Machine Learning, or related field, or equivalent practical experience.
- Familiarity with modern AI tooling and frameworks such as AWS Bedrock, LangChain, or vector databases.
- Experience building and operating ML workflows involving LLMs, including prompt-driven systems and model-assisted pipelines.
- Familiarity with orchestrating ML-driven decisions in high-throughput or low-latency environments (ranking, recommendation, optimization).
- Experience with applied ML for relevance, ranking, or personalization (feature engineering, evaluation, feedback loops).
- Experience working in small, fast-moving, cross-functional teams.
Fetch Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Fetch and has not been reviewed or approved by Fetch.
-
Healthcare Strength — Benefits information points to comprehensive medical, dental, vision, and life insurance coverage. Feedback suggests employees value the strong health offerings alongside mental-health support.
-
Leave & Time Off Breadth — Policies include flexible or unlimited PTO, paid holidays and sick days, bereavement (including pet) and natural-disaster leave. Feedback suggests time-off breadth is a standout element of the package.
-
Wellbeing & Lifestyle Benefits — Wellness programs, 1:1 coaching, Gympass, team workouts, and nutrition counseling are provided. Office and remote perks such as home-office stipends, snacks, and pet-friendly spaces further enhance lifestyle support.
Fetch Insights
What We Do
Fetch Rewards is a mobile app that connects and rewards everyday shoppers for buying the brands they love. Fetch gives users the easiest way to save on their purchases by simply scanning any grocery receipt, from any store. For our brand partners, Fetch helps them build long-term loyalty, and understand a true 360 degree view of purchase behavior.
Why Work With Us
We put people first - both in our culture, and in our product. Our culture is built on transparency, empowerment and accountability. Our product is built on putting our customers first in everything we do - from design, to privacy and security, to new features. The result is the rapid growth we all dream of being a part of. Come join the team!
Gallery


.png)






