Jobs / United States / Hinge Health INC
Staff Software Engineer, Growth
Hinge Health INC · 🇺🇸 San Francisco-HQ
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 13 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 6 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 Hinge Health INC paid sponsored hires in similar roles5 certified filings for “Senior Software Engineer - React Native” (Software Developers) in CA: $188k–$265k, median $214k. Most were filed at wage level IV (60%) — 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 — Hinge Health INC
The US Department of Labor certified 13 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 6 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 Hinge Health INC →
About the role
THE ROLE We’re looking for a Staff Engineer to join our Growth team and scale the programs that bring new members into Hinge Health. This team owns our member-to-member referral program end-to-end — the incentive mechanics, referral flows, and personalization systems that motivate existing members to refer colleagues and family members. This is a high-ownership, full-stack role. You’ll set technical direction, work closely with product and data science, and have a direct line to business outcomes like referral conversion, cost-per-acquisition, and incremental bookings. WHAT YOU’LL DO - Own the technical direction and roadmap for the member referral platform across the full stack — from frontend experiences to backend services and data pipelines. - Scale incentive and referral systems to handle growing member volume and complexity without degrading conversion or user experience. - Integrate ML model outputs (for example, propensity scores, personalized offers, and targeting signals) into referral surfaces to improve effectiveness. - Design, instrument, and analyze A/B experiments; work with data science to close the feedback loop between model outputs and product outcomes. - Partner with product, design, and analytics to define what to build and why, balancing short-term wins with long-term platform leverage. - Raise the engineering bar by driving code quality, system design standards, observability, and technical decision-making on the team. - Participate in the team’s weekly on-call rotation, helping ensure the reliability and timely support of the systems we build. WHAT WE’RE LOOKING FOR - Incentive & growth experience — a track record of designing or evolving systems that measurably shift user behavior through incentives, rewards, or social mechanics. Domain background matters less than demonstrated growth impact. - Personalization at scale — experience operationalizing ML model pipelines, model serving, A/B testing infrastructure, and feedback loops that connect model performance to product outcomes. - Full-stack depth — strong skills across technologies such as React, React Native, TypeScript, NestJS, GraphQL, Node.js, relational and non-relational databases, Docker, Kubernetes, AWS, and Redis. We don’t expect a perfect match on every technology, but you should be fluent in most. - Staff-level leadership — you’ve set technical direction for a team, influenced cross-functional roadmaps, and made architectural decisions that have held up over time. BASIC QUALIFICATIONS - Bachelor’s degree (or foreign equivalent) in Computer Science, Engineering, or a related technical field. - 4+ years of professional software engineering experience, including meaningful time working on production systems at scale. - Hands-on experience building and operating full-stack applications (for example, using React/React Native on the frontend and Node.js/TypeScript or similar on the backend). PREFERRED QUALIFICATIONS - Experience designing and scaling incentive, rewards, or referral systems that drive measurable user and business outcomes. - Experience integrating ML models into production systems (for example, model serving, feature pipelines, experimentation, and feedback loops). - Depth with modern web and service technologies such as React, React Native, TypeScript, NestJS, GraphQL, Node.js, relational and non-relational databases, Docker, Kubernetes, AWS, and Redis. - Proven experience setting technical direction for a team, owning architectural decisions, and driving high-quality execution in partnership with product and data science. - Experience with experimentation platforms, A/B testing frameworks, or ML feature stores. - Prior work at a consumer growth-focused company (for example, e-commer