Jobs / United States / Reddit INC

Senior Machine Learning Engineer

Reddit INC · 🇺🇸 Remote - United States · Remote

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 66 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 40 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 Reddit INC paid sponsored hires in similar roles6 certified filings for “Machine Learning Engineer” (Software Developers) in NY: $216k–$260k, median $233k. Most were filed at wage level II (50%) — 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.

Start free →

Or apply yourself on the official page →

Sponsor Radar — Reddit INC

66 H-1B filings certified since Oct 2025

The US Department of Labor certified 66 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 40 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 Reddit INC →

About the role

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: • Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities • Intelligent advertising systems including ranking, bidding, measurement, and optimization • Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals • Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems • Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement You’ll work on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. What You’ll Do • Design, build, and deploy production-grade machine learning models and systems at scale • Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring • Build scalable data and model pipelines with strong reliability, observability, and automated retraining • Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems. • Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions • Improve system performance across latency, throughput, and model quality metrics • Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment • Contribute to technical strategy, architecture, and long-term ML roadmap Basic Qualifications • 3-5+ years of experience building, deploying, and operating machine learning systems in production • Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals • ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs) • Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow) • Experience designing scalable ML pipelines, data processing systems, and model serving infrastructur

View the official posting →

Source: Greenhouse (employer board) First seen: 2026-08-13 Last confirmed: 2026-10-03 How our data works → Report this job

Similar opportunities