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# Staff Machine Learning Engineer

- **Company:** DOORDASH, INC.
- **Location:** San Francisco, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $242,800.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Data Analysis, C++ (Programming Language), Computer Programming, Content Analysis, Cursor, Information Retrieval, Python (Programming Language), Machine Learning, Natural Language Processing, Recommender Systems, Tensorflow, Software Engineering, Feature Engineering, Pytorch, Large Language Models, Claude Code, Prompt Engineering, Deep Learning, Generative AI, AI Coding Agents, Information Technology, Xgboost, Machine Learning Operations
- **Published:** October 11, 2026
- **Apply:** https://www.juju.com/job/1_doordash-7980080

## About the Role

You're excited about this opportunity because you will… + Own impactful ML systems: Build and improve models that directly have a large impact on top and bottom line financials. + Collaborate cross-functionally: Partner with engineering, analytics, product, and operations to iterate quickly, moving models from prototype to production + Shape the future: We're one of the fastest growing Ads platforms in the world and we're looking to take that even further!
We're excited about you because you have… + 5+ years of experience building, deploying, and scaling ML and AI models for large-scale, user-facing or data-intensive products. + 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 + BS, MS, or PhD in Computer Science, Engineering, or a related field, or equivalent practical experience. + Deep expertise in one or more of the following areas: deep learning, large language models, information retrieval, ranking and relevance, recommendation systems, natural language processing, or content understanding. + Strong programming skills in Python, Java, or C++, with hands-on experience using ML frameworks such as PyTorch, TensorFlow, or XGBoost. + Extensive experience across the full ML lifecycle, including data analysis, feature engineering, iterative model development, rigorous offline
and online evaluation, and ongoing monitoring and improvement. + Strong collaborator and communicator who thrives in fast-paced, cross-functional environments. + Product-minded and impact-driven, with a passion for applying cutting-edge ML and AI techniques to real-world problems.
Bonus Points For + Experience designing and deploying LLM-based systems, including prompt engineering and retrieval-augmented generation (RAG) architectures, Generative RecSys. + Experience solving large-scale, user-centric and content-centric personalization problems, including user modeling, retrieval, ranking, and relevance. + Demonstrated contributions to the ML community through open-source projects, publications, or applied research in areas such as ML, NLP, information retrieval, or related fields.