Jobs / United States / Tower Research Capital LLC
GPU Systems Engineer
Tower Research Capital LLC · 🇺🇸 New York
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 44 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 9 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 Tower Research Capital LLC paid sponsored hires in similar roles9 certified filings for “Software Engineer I” (Software Developers) in NY: $150k–$190k, median $150k. Most were filed at wage level I (67%) — 1 lottery entry, ≈15% 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 — Tower Research Capital LLC
The US Department of Labor certified 44 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 9 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 Tower Research Capital LLC →
About the role
Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities. Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization. Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance. At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do — combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best. At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential. Summary: Trading and research at the firm run around the clock and across the globe, and they run on infrastructure this team designs, builds, and operates. As part of R&D, you will join the engineers responsible for the compute, storage, operating systems, and automation behind that work at serious scale: hundreds of petabytes of storage and large CPU and GPU clusters spanning thousands of nodes. The role is broad by design. One week you might be shaping the architecture of a new AI cluster, the next profiling a training job that will not scale, the next writing automation that keeps the whole fleet healthy with minimal human intervention. Responsibilities: • Design, deploy, and scale distributed GPU clusters, from hardware selection and network topology through to production operation. • Track down performance bottlenecks across the full stack: compute, storage, network, and the seams between them. • Partner with researchers to profile and benchmark GPU workloads, then turn the findings into measurable speedups. • Build the automation that lets a small team operate thousands of nodes: provisioning, monitoring, diagnostics, and self-healing. • Own infrastructure projects end to end, from scope and design through implementation and long-term support. • Qualify new generations of hardware and software, and work directly with vendors to root-cause complex issues. Qualifications: • 5+ years engineering large-scale Linux systems in HPC, AI, or distributed-infrastructure environments. • Deep Linux fundamentals: installation, performance tuning, and debugging, down to the kernel when the problem calls for it. • Hands-on troubleshooting of distributed GPU workloads, with a strong mental model of GPU performance. • Working experience with GPUDirect RDMA. You understand how data moves between GPUs and the network, and what to check when it does not. • Solid Python for automation and tooling, plus CUDA or C/C++ experience. You can read, profile, and debug GPU code, not just operate the clusters it runs on. • Familiarity with configuration management tools such as Salt, Ansible, Puppet, or Chef. • Comfort diagnosing problems that cross hardware, OS, and network boundaries rather than stopping at one layer. • Clear communication. You wil