> Markdown version of [/jobs/ext/1984977-staff-machine-learning-engineer-shopping-ads](https://www.wearedevelopers.com/jobs/ext/1984977-staff-machine-learning-engineer-shopping-ads). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Machine Learning Engineer, Shopping Ads - **Company:** reddit Inc. - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Machine Learning, Azure Machine Learning, Model-Driven Development, Feature Engineering, Low Latency, Machine Learning Operations - **Published:** August 8, 2026 - **Apply:** https://us.experteer.com/career/view-jobs/staff-machine-learning-engineer-shopping-ads-usa-58859340 ## About the Role * Apply state-of-the-art ML approaches to production problems and choose architectures based on measurable benefit * Design systems balancing prediction quality with latency, throughput, reliability, and cost * Drive cross-team initiatives across Shopping Ads, Catalog, ML Platform, and more * Mentor engineers and technical leads, clarifying ownership and guiding execution in ambiguity * Stay current with advances in ads optimization, commerce recommendation, and production ML systems Tasks * 7+ years of professional software or ML engineering experience with production ML systems * Experience building end-to-end models or model-driven products that improve advertising, recommendation, search, or marketplace performance * Experience optimizing low-funnel metrics such as conversion, revenue, or ROAS * Hands-on experience with model development, feature engineering, pipelines, online inference, and experimentation * Proven track record delivering complex results requiring multiple systems or teams * Experience applying modern ML models in production with measurable improvements * Proven technical leadership: setting direction, architecture, mentoring, and cross-functional influence * Strong understanding of large-scale, high-throughput, low-latency ML systems and trade-offs * Excellent communication and collaboration skills with ability to align teams on long-term vision Key requirements * Comprehensive Healthcare Benefits and Income Replacement Programs * 401k with Employer Match * Flexible Vacation & Paid Volunteer Time Off * Generous Paid Parental Leave * Family Planning Support * Mental Health & Coaching Benefits ## Description Experteer Overview As Staff ML Engineer for Shopping Ads, you will steer the technical strategy and end-to-end ML delivery across targeting, retrieval, ranking and conversion models to improve advertiser outcomes. You'll collaborate with cross-functional teams to align business goals with scalable ML systems, shape feature representations, and ensure delivery quality and efficiency. This role offers hands-on leadership in production ML, with impact on large-scale ads experiences and marketplace health. Compensation / Benefits * Lead ML strategy and architecture for Shopping Ads delivery across targeting, retrieval, ranking, engagement, conversion and value optimization * Own end-to-end model development from opportunity sizing to online deployment and monitoring * Build and optimize models for low-funnel advertiser objectives while maintaining relevance and user experience * Develop feature representations connecting user intent, context, catalog signals, advertiser signals, and history * Apply state-of-the-art ML approaches to production problems and choose architectures based on measurable benefit * Design systems balancing prediction quality with latency, throughput, reliability, and cost * Drive cross-team initiatives across Shopping Ads, Catalog, ML Platform, and more * Mentor engineers and technical leads, clarifying ownership and guiding execution in ambiguity * Stay current with advances in ads optimization, commerce recommendation, and production ML systems Tasks * 7+ years of professional software or ML engineering experience with production ML systems * Experience building end-to-end models or model-driven products that improve advertising, recommendation, search, or marketplace performance * Experience optimizing low-funnel metrics such as conversion, revenue, or ROAS * Hands-on experience with model development, feature engineering, pipelines, online inference, and experimentation * Proven track record delivering complex results requiring multiple systems or teams * Experience applying modern ML models in production with measurable improvements * Proven technical leadership: setting direction, architecture, mentoring, and cross-functional influence * Strong understanding of large-scale, high-throughput, low-latency ML systems and trade-offs * Excellent communication and collaboration skills with ability to align teams on long-term vision Key requirements * Comprehensive Healthcare Benefits and Income Replacement Programs * 401k with Employer Match * Flexible Vacation & Paid Volunteer Time Off * Generous Paid Parental Leave * Family Planning Support * Mental Health & Coaching Benefits ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [What is relational learning and why does it matter?](https://www.wearedevelopers.com/videos/396-what-is-relational-learning-and-why-does-it-matter) - [Swapping Low Latency Data Storage Under High Load](https://www.wearedevelopers.com/videos/746-swapping-low-latency-data-storage-under-high-load) - [Navigating the AI Revolution in Software Development](https://www.wearedevelopers.com/videos/1266-navigating-the-ai-revolution-in-software-development) - [How Machine Learning is turning the Automotive Industry upside down](https://www.wearedevelopers.com/videos/61-how-machine-learning-is-turning-the-automotive-industry-upside-down) ## Related Articles - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Dev Digest 119 - ❤️ === ❤️](https://www.wearedevelopers.com/magazine/454-dev-digest-119)