Jobs / United States / Airbnb
Senior Staff Machine Learning Engineer, Growth Platform Engineering
Airbnb · 🇺🇸 Remote - USA · 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 167 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 71 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 Airbnb paid sponsored hires in similar roles8 certified filings for “Machine Learning Engineer” (Data Scientists) in WA: $179k–$196k, median $185k. 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.
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Sponsor Radar — Airbnb
The US Department of Labor certified 167 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 71 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 Airbnb →
About the role
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Growth Platform team’s vision is to drive long term sustainable growth for the Airbnb community. Our mission is to build a best-in-class agentic system, and capabilities to support the growth of all Airbnb products, current and future. We achieve this by delivering highly personalized and relevant content and product experiences to the Airbnb community, both on and off of the Airbnb platform. The north star is full autonomy — where AI identifies opportunities, creates campaigns, personalizes experiences, and optimizes outcomes with minimal human intervention. We are progressing along a deliberate maturity curve: AI assisted → agentic → autonomous, with human-in-the-loop controls at every stage to ensure brand safety, quality, and compliance. The Growth Platform deeply integrates with the Airbnb product, understanding the customer journey and enabling differentiated customer engagement experiences to drive product growth. The platform also powers digital marketing channels including landing pages, email, push, SMS, and digital advertising, as well as the machine learning/AI and data platforms that feed into the management and optimization of these channels. The Difference You Will Make: • As a machine learning engineer or scientist, your expertise will be pivotal in developing AI-powered solutions to shape the future of the Airbnb agentic growth platform with cutting-edge AI techniques. You will drive and guide the rest of the engineers to brainstorm, design and develop AI products and features from inception to production. • We're seeking a Senior Staff Engineer who thrives at the intersection of technical depth , architectural thinking , and mentorship . • You’ll collaborate with cross-functional leaders, build resilient systems that operate globally at scale, and help evolve the foundational building blocks behind AI-powered growth systems. Some example projects you will work on: • AI-Powered Content Generation - Developing agentic capabilities to autonomously create personalized emails, push notifications, Ad copy, and creatives. This significantly scales marketing efforts by enabling more campaigns, greater variant testing, and faster iteration cycles. • ML/AI Orchestration for Decisioning - Utilizing AI to determine the optimal audience, message, channel, and timing for communications. This shifts marketing decision-making to model-driven intelligence, enhancing relevance and minimizing message fatigue. The direct impact is an uplift in engagement rates, conversion, and ultimately, bookings. • Proactive Marketing Analyst Agent - Designing an AI agent that autonomously identifies new marketing opportunities and converts them into executable campaigns. It leverages world knowledge, proprietary Airbnb intelligence, and deep customer profiles. A crucial performance-based feedback loop ensures the system continuously learns from campaign outcomes to refine and improve future recommendations. A Typical Day: • Work with large scale structured and unstructured data; explore, experiment, build and continuously improve Machine Learning models and pipelines for Airbnb product, business and operational use cases. • Work collaboratively with cross-functional partners including product managers, operations and data scientists, to identify opportunities for business impact; understand, refine, and prioritize requirements for machine learni