Build and improve machine learning systems for ad ranking, relevance, personalization, and optimization. Responsibilities include feature pipelines, model training and evaluation, active learning, LLM-assisted labeling and synthetic data generation, experimentation, and low-latency production inference. The role partners with product, data, and platform teams to improve advertiser performance and user engagement while maintaining reliability, latency, and data quality.
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 Ads Platform team. This role sits at the intersection of applied machine learning, data engineering, and production systems, with a focus on building and improving ranking, relevance, and optimization models that drive ad selection and delivery at scale. You will partner closely with product, data, and platform teams to develop ML-driven decisioning systems, including feature pipelines, model training and evaluation workflows, and low-latency serving infrastructure. This is a high-impact opportunity to influence how ads are ranked and personalized across the Fetch experience, improving advertiser performance, user engagement, and overall marketplace efficiency.
Role Responsibilities:
- 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.
Minimum Requirements:
- 5+ 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.
Preferred Requirements:
- 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.
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.
- 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. 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. (Holidays will vary for Canada-based roles)
- 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: 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 for US-based roles. 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 [email protected].
Similar Jobs
Enterprise Web • Fintech • Payments • Software • Financial Services
The Director of Sales will independently manage complex enterprise sales for Narmi One, targeting community and regional financial institutions. Responsibilities include prospecting, pipeline development, discovery, demonstrations, business case creation, procurement, legal due diligence, proposal development, quota attainment, new customer acquisition, and expansion sales. The role requires strong financial-institution relationships, consultative selling, complex deal negotiation, cross-functional collaboration, and travel of 25–40%.
Top Skills:
Account OpeningAi-Powered Fraud PreventionDigital BankingLendingNarmi OneNarmi PlatformReal-Time Payments
Enterprise Web • Fintech • Payments • Software • Financial Services
The Growth Executive sells Narmi One, a digital banking SaaS platform, to community banks and credit unions. Responsibilities include building executive relationships, generating outbound opportunities, managing the full enterprise sales cycle, negotiating and closing six-figure ARR contracts, collaborating with marketing and cross-functional deal teams, maintaining CRM data, and driving upsell initiatives. The role requires consultative selling, complex solution expertise, financial-institution relationships, and consistent quota performance.
Top Skills:
Ai-Powered Fraud PreventionCRMEnterprise Saas
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Leads Chevrolet sales and aftersales performance across a dealership zone. Builds dealer relationships, develops District Sales Managers, analyzes market and sales data, drives market share and profitability, oversees dealer compliance and digital marketing execution, manages inventory performance, and implements customer retention and business growth strategies. The role is field-based, requires frequent travel, and includes team coaching, dealer negotiations, and strategic planning.
Top Skills:
Data Visualization ToolsGoogle WorkspaceReporting ToolsSpreadsheet Software
What you need to know about the Colorado Tech Scene
With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute
