Jobs / United States / Anthropic Pbc D B A Anthropic INC
Staff Research Engineer, Discovery Team
Anthropic Pbc D B A Anthropic INC · 🇺🇸 San Francisco, CA
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordUSCIS Data Hub records 1 H-1B approvals for this employer in FY2023. Source: USCIS H-1B Employer Data Hub (US Citizenship and Immigration Services).
- 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.
- 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 — Anthropic Pbc D B A Anthropic INC
USCIS Data Hub records 1 H-1B approvals for this employer in FY2023. Source: USCIS H-1B Employer Data Hub (US Citizenship and Immigration Services).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Anthropic Pbc D B A Anthropic INC →
About the role
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team Our team is organized around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier. Our team likes to think across the whole model stack. Currently the team is focused on improving models' abilities to use computers – as a laboratory for long horizon tasks and a key blocker to many scientific workflows. About the role As a Research Engineer on our team you will work end to end, identifying and addressing key blockers on the path to scientific AGI. Strong candidates should have familiarity with language model training, evaluation, and inference, be comfortable triaging research ideas and diagnosing problems and enjoy working collaboratively. Familiarity with performance optimization, distributed systems, vm/sandboxing/container deployment, and large scale data pipelines is highly encouraged. Join us in our mission to develop advanced AI systems that are both powerful and beneficial for humanity. Responsibilities: • Working across the full stack to identify and remove bottlenecks preventing progress toward scientific AGI • Develop approaches to address long-horizon task completion and complex reasoning challenges essential for scientific discovery • Scaling research ideas from prototype to production • Create benchmarks and evaluation frameworks to measure model capabilities in scientific workflows and computer use • Implement distributed training systems and performance optimizations to support large-scale model development You may be a good fit if you: • Have 8+ years of ML research experience • Are familiar with large scale language model training, evaluation, and inference pipelines • Enjoy obsessively iterating on immediate blockers towards longterm goals • Thrive working collaboratively to solve problems • Have expertise in performance optimization and distributed computing systems • Show strong problem-solving skills and ability to identify technical bottlenecks in complex systems • Can translate research concepts into scalable engineering solutions • Have a track record of shipping ML systems that tackle challenging multi-step reasoning problems Strong candidates may also have: • Expertise with performance optimization for language model inference and training • Experience with computer use automation and agentic AI systems • A history working on reinforcement learning approaches for complex task completion • Knowledge of containerization technologies (Docker, Kubernetes) and cloud deployment at scale • Demonstrated ability to work across multiple domains (language modeling, systems engineering, scientific computing) • Have experience with VM/sandboxing/container deployment and large-scale data processing • Experience working with large scale data problem solving and infrastructure • Published research or practical experience in scientific AI applications or long-horizon reasoning The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $350,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A fie