# Senior ML Operations Engineer II - Monetization at Fetch

Fetch is hiring a Senior ML Operations Engineer II - Monetization for a remote role open to applicants in United States. Level rates it Little AI ●○○○; you can [apply on Fetch](https://jobsbylevel.com/go/a5fb6d91-8184-4a4a-9324-a5554ac6a587?utm_medium=ai-agent).

AI Level 1, AI centrality 22 out of 100. Remote (United States - Remote).

## Details

- Company: [Fetch](https://jobsbylevel.com/companies/fetch)
- AI level: AI Level 1 (score 22 out of 100)
- Location: Remote (United States - Remote)
- Posted: October 20, 2026
- Apply: https://jobsbylevel.com/go/a5fb6d91-8184-4a4a-9324-a5554ac6a587?utm_medium=ai-agent

## Description

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.
Role Responsibilities
Own the complete model lifecycle from experimentation through validation, deployment, versioning, retraining, rollback, and retirement.
Establish clear model promotion criteria, release processes, and rollback paths that enable teams to ship improvements confidently.
Build monitoring for data quality, drift, prediction quality, service reliability, latency, and infrastructure cost.
Partner with data scientists to define meaningful offline and production evaluation signals, including for use cases with delayed outcome labels.
Use production evidence to improve model performance, platform reliability, deployment speed, and infrastructure efficiency.
Build reusable training, evaluation, and deployment pipelines that support multiple models and modeling approaches.
Develop dependable orchestration workflows covering dependencies, scheduling, retries, backfills, and failure recovery.
Translate scientific requirements into maintainable production systems with clear interfaces, ownership, and operational expectations.
Build and maintain an accessible model hub connecting model documentation, evaluation results, release history, versioning, and monitoring.
Create tested CI/CD workflows, reproducible environments, actionable alerts, incident-response procedures, and operational runbooks.
Define MLOps priorities in partnership with Data Science and Engineering, identifying risks before they become production issues.
Establish reusable engineering standards, mentor teammates, and reduce the operational burden placed on data scientists.
Minimum Requirements
5+ years managing production ML systems beyond initial deployment, including monitoring, retraining, incident response, and continuous improvement.
Strong production software development skills in Python and proficiency with SQL.
Hands-on experience using Spark for distributed data processing.
Experience with a workflow orchestration engine for scheduling, dependency management, retries, backfills, and recovery.
Hands-on experience building infrastructure

The description is cut here. Read the full offer: https://jobsbylevel.com/jobs/senior-ml-operations-engineer-ii-monetization-at-fetch-68ffdc

Source: https://jobsbylevel.com/jobs/senior-ml-operations-engineer-ii-monetization-at-fetch-68ffdc

## Cite this page

Level. https://jobsbylevel.com/jobs/senior-ml-operations-engineer-ii-monetization-at-fetch-68ffdc.

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