Jobs / United States / Uber

Staff Machine Learning Engineer

Uber · 🇺🇸 Chicago, IL; New York, NY; San Francisco, CA; Seattle, WA; 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 689 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. 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 Uber paid sponsored hires in similar roles237 certified filings for “Software Engineer” (Software Developers) in CA: $191k–$239k, median $213k. Most were filed at wage level III (38%) — 3 lottery entries, ≈46% 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).

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Sponsor Radar — Uber

689 H-1B filings certified since Oct 2025

The US Department of Labor certified 689 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. 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 Uber →

About the role

About the Role Uber Freight Marketplace is building the next generation of logistics technology by leveraging Uber's proven marketplace playbook to freight. As part of a small, high-impact team, you'll help bring expertise from Uber's mobility and delivery marketplaces into a rapidly evolving industry, developing pricing, matching, recommendation, and optimization systems that will disrupt the freight industry ($1T TAM). Uber Freight is at a very early stage, with just 0.4% of the pie now, and it's a rare opportunity to solve challenging marketplace problems with AI/ML and marketplace optimization while shaping how the freight industry transforms. We are looking for a highly motivated Machine Learning Engineer to join Uber's Marketplace team to modernize the Uber Freight marketplace team. It is a fascinating area with challenges in predictive modeling, causal inference, constrained optimization, reinforcement learning, marketplace design, etc. The business is about to elevate and this role has a huge growing opportunity. What You'll Do This role requires end to end ownership for the ML models in UF marketplace (cost prediction, booking probability, demand elasticity, etc.). While your job is mostly about model development, you will work with backend engineers together to put them in production and make sure they work as expected. Basic Qualifications • 6+ years of experience developing ML models to solve business problem. • Bachelor's degree in Computer Science, Computer Engineering, or related fields. • Familiar with modern AI/ML frameworks (e.g., PyTorch). Preferred Qualifications • Product experience will be a big plus for this role. Adaptive development of ML models to the business context is critical. • Previous experience with state-of-the-art marketplace technology is preferred. • Experience with causal inference and constrained optimization For Chicago, IL-based roles: The base salary range for this role is USD $209,000 per year - USD $232,000 per year. For New York City, NY-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. Ready to Ride? This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you. You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits. Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requi

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Source: The Muse feed First seen: 2026-10-09 Last confirmed: 2026-10-09 How our data works → Report this job

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