Jobs / United States / Doordash INC
Machine Learning Engineer, Marketplace Optimization
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
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 mission of the Marketplace Optimization team is to ensure we maintain a healthy Ads Marketplace across all our verticals for both search (query context) and discovery experiences while fulfilling the requirements of all players in this marketplace. Marketplace Optimization is a critical part of the Ads Delivery funnel with a broad charter responsible for Bidding, Auction Design, Budget Pacing, Forecasting, and Ads Experimentation. Our work directly shapes advertiser experience, consumer experience, and marketplace balance. We leverage artificial intelligence and advanced ML, deep learning techniques to power decision-making in real time — from optimizing ad auctions to generating the most efficient bids and pacing budgets dynamically. These models sit at the heart of DoorDash’s ad delivery and play a pivotal role in improving the efficiency, fairness, and scalability of our marketplace. The opportunity is massive as DoorDash expands into new verticals like Grocery and Retail while building unique innovative ad products to leverage the closed loop marketplace. About the Role We’re looking for a Machine Learning Engineer to help design, build, optimize and scale large-scale ML systems within the Ads Delivery funnel. • Design, build, and deploy ML models and pipelines for pacing, bidding, auction and targeting optimization. • Collaborate with Data Science and Product teams to develop and evaluate new algorithms through rigorous experimentation. • Improve and scale existing ML infrastructure and data pipelines in partnership with Platform and Infra teams. • Write high-quality, maintainable code and participate in system design and peer reviews. • Learn from senior engineers and contribute to technical discussions that shape the team’s roadmap. • Partner with Data Science and Marketing to design and execute lift tests; collaborate with Platform teams on budget A/B testing and evaluation framework. 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. • Drive experimentation: Rapidly test hypotheses via robust sequential experiments; measure and explain your models’ impact on marketplace KPIs • Optimize at scale: Work with one of the largest delivery datasets, building optimization pipelines that consider budget, fairness, assignment rates, and more • 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… • B.S., M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or a related field. • 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 • Industry experience building or maintaining machine learning systems in production. • Solid understanding of machine learning fundamentals, statistics, and data modeling. • Strong programming skills in Python, Java, or C++, and experience with ML frameworks such as TensorFlow, PyTorch, or XGBoost. • Excellent communication and collaboration skills — comfortable working with cross-functional partners in Product, DS, and Engineering. • Curiosity and a growth mindset — motivated to learn, iterate quickly, and take ownership of impactful projects