Remote Machine Learning Engineer Jobs (No ghost jobs, direct from employers)

  • 105 companies
  • $226K median pay
  • 100% remote

Machine learning engineer jobs you can do from home, checked every hour. Every posting shows pay where listed, posting age, company reviews and a ghost-job check, so you apply only where someone is hiring.

120 jobs found

  • 4 days agoLow ghost risk
    UberRemoteNew York City, NY$232K - 258KLead
  • 1 day agoLow ghost risk
    WoolworthsRemoteSurry Hills, NSW$105K - 140KMid-level
  • 1 day agoLow ghost risk
    Ria FinancialRemoteVilnius$70K - 110KSenior
  • 1 week agoLow ghost risk
    QualcommRemoteSan Diego, CA$135K - 203KMid-level
  • 2 days agoModerate ghost risk
    hims & hersRemote$180K - 250KLead
  • 2 days agoLow ghost risk
    QualcommRemoteSan Diego, CA$162K - 243KMid-level
  • 14 hours agoLow ghost risk
    UberRemoteSeattle, WA$267K - 297KLead
  • 5 days agoLow ghost risk
    Hyatt Hotels Corp.Remote$120K - 180KSenior
  • 6 days agoLow ghost risk
    UberRemoteSan Francisco, CA$202K - 224KSenior
  • 6 days agoLow ghost risk
    EmpowerRemote$180K - 240KLead
  • 6 days agoLow ghost risk
    UberRemoteNew York City, NY$202K - 224KSenior
  • 6 days agoLow ghost risk
    UberRemoteSan Francisco, CA$202K - 224KSenior
  • 2 days agoLow ghost risk
    QualcommRemoteNew York City, NY$224K - 335KMid-level
  • 1 week agoLow ghost risk
    Babylist, IncRemote$234K - 291KMid-level
  • 2 days agoLow ghost risk
    Siemens EnergyRemoteSarajevo$35K - 60KMid-level
  • 5 days agoLow ghost risk
    Hyatt Hotels Corp.Remote$120K - 180KSenior
  • 2 days agoLow ghost risk
    QualcommRemoteSanta Clara, CA$174K - 261KLead
  • 2 days agoLow ghost risk
    QualcommRemoteSan Diego, CA$174K - 261KLead
  • 1 day agoLow ghost risk
    Nebius Group NVRemotePalo Alto, CA$195K - 262KSenior
  • 1 week agoLow ghost risk
    InstacartRemote$230K - 291KLead

Staff Machine Learning Engineer

Uber

4 days agoRemoteNew York City, NY$232K - 258KLead

Why this job matches

See how well your resume fits this job and what it is missing.

About the Role

Uber Marketplace is at the heart of Uber's business, with Rider Pricing playing a critical role by setting prices and targeting promotions for Uber riders. Our team's mission is to drive revenue growth, ridership growth and Uber's profitability through advanced machine learning and data science. We build reliable, scalable platforms that optimize rider pricing in both real-time and offline systems, including baseline trip pricing and targeted discounts.

The Rider Pricing team is a fast-moving, high-opportunity space where you'll have the chance to make a significant impact on the business. On this team, your work will affect over 95% of Uber's mobility business revenue. You'll take ownership of one key pillar of the rider pricing domain and lead the technical direction for improving our pricing algorithms, optimization algorithms and models. You will work across ML, serving, and optimization system components, and set technical direction for modeling best practices across model building, evaluation and deployment.

In this role, you'll apply advanced machine learning technologies, including deep learning, generative AI for causal modeling, representation learning and personalization, to optimize Uber's pricing. You will also work with serving infrastructure and product teams to design and evolve the rider pricing systems to support new product and algorithm evolutions and drive Uber's top-line rider and revenue growth.

What You'll Do

  • Lead a group of SWEs and MLEs working on Uber's rider pricing to develop and implement new machine learning and optimization techniques powering billions of rides around the world, and helping riders achieve their mobility needs.
  • Improve the performance of models and algorithms powering pricing algorithms and promotion targeting.
  • Own the problem E2E, including working with cross-functional teams to define the product and/or technical roadmap.
  • Mentor more junior team members by role modeling ML best practices. Collaborate with cross-functional teams to ensure alignment and drive Uber's ridership and revenue growth. Help Uber's end-users by making mobility options accessible and affordable.

Basic Qualifications

  • Masters degree in Computer Science, Engineering, Mathematics, or a related field, with 7+ years of full-time engineering experience.
  • Proficiency in one or more programming languages (e.g., C, C++, Java, Python, Go).
  • Experience with machine learning and optimization algorithms.

Preferred Qualifications

  • PhD in Computer Science, Engineering, Mathematics, or a related field, with 2+ years of full-time engineering experience.
  • Experience solving complex business problems by translating them into machine learning and optimization solutions.
  • Familiarity with large-scale data systems (e.g., Spark, Hive) and experience building production-ready algorithmic systems.
  • Strong background in deep learning, generative AI, causal modeling, and reinforcement learning.

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 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 requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

Company Reviews

Employee reviews

3.8

35,666 Reviews
  • 539 %
  • 428 %
  • 319 %
  • 27 %
  • 17 %
  • Good place sonetime hectic
    2026-03-09T20:01:45.657

    Pros: Pay, culture, smart people, impactful work

    Cons: Sometimes hectic, slow growth. Nothing else

  • Toxic in general, different by teams
    2026-03-09T08:32:26.780

    Pros: Marketing team is great Push for innovation Fast paced

    Cons: Ops team is toxic Politics is high Fast paced

  • low pay
    2026-03-08T17:47:06.657

    Pros: your own time work if you want

    Cons: Not enough pay not enough requests

Related jobs by role, place and level

Every page lists all openings, with likely ghost jobs flagged. Checked every hour.

Frequently asked questions about remote machine learning engineer jobs

What is a ghost job?

A ghost job is a posting for a role the company isn't actively hiring for. Some stay up after the company fills the role. Others collect resumes for an opening that may never come.

You spend an evening tailoring an application, and nobody on the other side is looking for you.

What do remote machine learning engineer jobs pay?

Across the postings here that list pay, the median is about $226,000 a year. Most of these postings list a pay range.

How many remote machine learning engineer jobs are there?

At our last count there were about 120 open postings from about 100 employers. The list on this page is live, so the count above it is the current one.

Are these jobs fully remote?

This page lists only postings the employer marked as remote. Many are still tied to a country or a time zone, so check the location on the posting before you apply.

How does Enhancv spot a ghost job?

Every posting goes through five checks: how long it has been up, whether a salary is posted, what employees say about the company, how specific the description is and whether it lists real requirements. Each job shows the checks it passed and the ones it didn't.

How fresh are the job postings?

Enhancv checks postings every hour, and every job shows how long ago it went up. Most hires happen within 30 days of posting. A listing that's been open for two months raises its ghost job risk.