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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Machine Learning Engineer - **Company:** DOORDASH, INC. - **Location:** New York, NY, United States (Remote available) - **Experience:** Expert - **Salary:** $137,100.0 - $201,600.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, C++ (Programming Language), Computer Programming, Data Retention, Cursor (Graphical User Interface Elements), Python (Programming Language), Machine Learning, Tensorflow, Software Engineering, Pytorch, Build Management, Information Technology, Xgboost, Machine Learning Operations - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/staff-machine-learning-engineer-dashpass-doordash-usa-8074822 ## About the Role * M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or a related field. * 8+ years of industry experience building production-scale ML systems. * Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software * Strong understanding of probability theory, statistics, and machine learning fundamentals. * Strong programming skills in Python, Java, or C++, and experience with ML frameworks such as TensorFlow, PyTorch, or XGBoost. * Interest in building and leading a new team that has broad impact across a wide range of problem spaces to support a critical business line. * Proven ability to lead cross-functional initiatives and drive complex technical projects end-to-end. * Excellent communication skills - able to explain technical concepts to product, business, and engineering audiences. * Experience in subscriptions growth or marketplace systems is a plus. ## Description We're looking for a Staff Machine Learning Engineer to drive the design and development of large-scale ML/optimization systems to target personalization efforts across the DashPass Subscriber journey., * Contribute to Causal inference modeling to measure the incremental impact of DashPass Subscriber acquisition and retention strategies. * Incentive optimization frameworks that personalize progressive rewards to improve spend efficiency. * Budget allocation and forecasting models that identify optimal spend across acquisition, referrals, and retention. * Partner closely with Product, Data Science, and Engineering teams to design experiments, model frameworks, and production ML systems that directly impact DashPass subscriber growth metrics. * Provide technical mentorship and guidance to engineers and cross-functional partners - leading through influence, not management. * Build and deploy 0*1 ML systems that improve subscriber outcomes and marketplace health. * Set best practices for model training, evaluation, deployment, and monitoring This is a highly impactful IC role for someone who enjoys combining economic intuition, large-scale ML modeling, and system design to solve complex real-world optimization problems., How it works: Gem assists our recruiting team by evaluating job related qualifications and characteristics in connection with hiring. The tool is designed and used to support - rather than replace - human decision-making; trained personnel make final decisions with meaningful human review and oversight, and DoorDash does not use Gem or other AI-enabled tool in a manner that has the effect of subjecting applicants or employees to discrimination based on any protected characteristic or proxy or for engaging in any protected activity under applicable law. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [TikTok's Privacy Innovation](https://www.wearedevelopers.com/videos/1036-tiktok-s-privacy-innovation) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [How We Built a Machine Learning-Based Recommendation System (And Survived to Tell the Tale)](https://www.wearedevelopers.com/videos/752-how-we-built-a-machine-learning-based-recommendation-system-and-survived-to-tell-the-tale) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Why Upskilling And Reskilling is Important For Developers](https://www.wearedevelopers.com/magazine/428-why-upskilling-and-reskilling-is-important-for-developers) - [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies)