Jobs / United States / Doordash INC

Senior Staff Machine Learning Engineer

Doordash INC · 🇺🇸 San Francisco, CA; Sunnyvale, CA

Sponsorship verdict

Sponsorship possible

One solid signal, not two — worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 396 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 147 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
  • What Doordash INC paid sponsored hires in similar roles15 certified filings for “Software Engineer, Machine Learning” (Data Scientists) in CA: $169k–$217k, median $188k. Most were filed at wage level II (43%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
  • Confirmed live todayWhen a source last listed this job as open.

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.

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Sponsor Radar — Doordash INC

396 H-1B filings certified since Oct 2025

The US Department of Labor certified 396 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 147 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).

Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Doordash INC →

About the role

About the Team The Ads & Promos Delivery team powers the last-mile delivery of ads and promotions, two marketing products offered to merchants, connecting merchant intent with consumer demand across search and discovery experiences. As a Senior Staff Engineer, you will lead the technical direction for AI-first experiences, including ranking and relevance systems that sit at the core of our ads marketplace and shape how ads are selected, ordered, and personalized in real time across all verticals. You will design and build next-generation AI-first ranking systems using state-of-the-art techniques such as sequence modeling, deep learning, and large language models (LLMs). Your work will span query understanding, user and merchant representation learning, contextual relevance, and multi-objective optimization, balancing advertiser value, consumer experience, and marketplace health at scale. You will set the long-term technical vision, drive cross-team alignment, and translate cutting-edge research into production systems that operate under strict latency, scale, and reliability constraints. As DoorDash expands into 40+ global markets and new verticals such as Grocery and Retail, this role offers a rare opportunity to define how modern AI, including sequential models and LLM-powered decisioning, reshapes ads relevance in a closed-loop marketplace. About the Role • Apply state-of-the-art machine learning and LLM techniques to problems across personalization, query understanding, user and content understanding. • Rigorously evaluate ML and LLM models using a combination of offline analysis and online experimentation, designing metrics and experiments that clearly measure quality, impact, and tradeoffs. • Own the full model lifecycle from research to production, including data analysis, model development, evaluation, offline and online A/B testing, and continuous iteration. • Partner closely with product managers, data scientists, and designers to ensure AI-driven systems deliver meaningful, user-facing improvements. • Stay at the forefront of ML and AI innovation by assessing emerging research and translating promising approaches into scalable, production-ready systems. This is a high-impact role for someone who enjoys combining economic intuition, large-scale ML modeling, and applied engineering to solve complex real-world optimization problems. 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 engineerin

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Source: Greenhouse (employer board) First seen: 2026-08-17 Last confirmed: 2026-10-03 How our data works → Report this job

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