Jobs / United States / Reddit INC
Machine Learning Manager, Feed Ecosystems
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 roles1 certified filing for “Senior Engineering Manager, Machine Learning” (Computer and Information Systems Managers) in NY: $328k–$328k, median $328k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% 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 — Reddit INC
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 . Reddit is looking for an experienced Engineering Manager to lead our Feed Ecosystems team. In this role, you’ll lead a high-impact team of Machine Learning Engineers focused on building recommendation systems that support sustainable growth across users, posts, and communities. Your team will improve relevance for new, low-signal, and logged-out users; help new posts and communities find the right audiences; and develop ML systems that balance personalization, discovery, and ecosystem quality across Reddit’s 100,000+ active communities. If applying ML / AI in production to improve Reddit Relevance and strengthen Reddit’s community ecosystem excites you, then you’ve found the right place. Responsibilities: • Define Technical Vision & Strategy: Define the technical vision and long-term roadmap for Feed Ecosystems, aligning recommender-system investments with Reddit’s goals around user growth, contribution, community health, and high-quality discovery. • Team Leadership & Development: Coach and support the development of your team, constantly seeking opportunities to grow their skills and impact. • Cross-Functional Partnership: Work closely with product, design, data science, safety, community, ads, and platform partners to identify opportunities, set expectations, and communicate your team’s work. • Technical Execution & Delivery: Oversee the design, development, and optimization of ML systems that improve cold-start relevance, new post and community distribution, community discovery, and feed quality. • Quality & Ecosystem Measurement: Help define and operationalize signals for subjective and objective quality, ensuring Feed systems optimize not only for engagement, but also for user value, community health, contribution, and long-term ecosystem outcomes. • Platform & Infrastructure Collaboration: Collaborate with platform and infrastructure teams to build scalable AI-powered systems that support discovery, personalization, and healthy content distribution across Reddit. • Operational Excellence: Maintain high standards for system performance, reliability, efficiency, and responsible AI practices in alignment with user needs and ecosystem health. • Recruiting & Growth: Partner with our recruiting team to attract, interview, and hire diverse and talented machine learning engineers, growing a world-class team. Qualifications: • Experience Leading ML Teams: 2+ years of experience building and managing high-performing ML or recommender-systems teams. • Deep ML Expertise: Hands-on experience with large-scale production ML systems, ideally including recommender systems, personalization, cold-start modeling, content understanding, or LLM-powered recommendation applications. • Technical Domain Knowledge: Strong understanding of recommender systems, including candidate retrieval, ranking, value modeling, ecosystem dynamics, and measurement strategies. • Strategic Thinking: Ability to develop and communicate a clear, compelling technical strategy across ambiguous problem spaces, balancing user relevance, community growth, content quality, safety, and business impact. • Impact-Driven Mindset: Passion for developing scalable, well-designed, and responsible AI systems that improve user value while supporting a healthy and sustainable content ecosystem. • Exceptional Communication