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About the Role
Join engineers responsible for the compute, storage, operating systems, and automation behind trading and research operations at serious scale. The role is broad, involving shaping AI cluster architecture, profiling training jobs, and writing automation to maintain fleet health.
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.
Requirements
- 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. 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. Ability to read, profile, and debug GPU code.
- Familiarity with configuration management tools such as Salt, Ansible, Puppet, or Chef.
- Comfort diagnosing problems that cross hardware, OS, and network boundaries.
- Clear communication skills for daily interaction with researchers, engineers, and vendors.
Skills
- Linux
- HPC
- AI
- Distributed Infrastructure
- GPU
- GPUDirect RDMA
- Python
- CUDA
- C/C++
- Salt
- Ansible
- Puppet
- Chef
- NCCL
- NVLink
Location
- NYC
Work Type
- Hybrid
Experience Level
- 5+ years
Salary/Compensations
- $200,000-$300,000
Benefits
- Discretionary bonus
- Generous paid time off policies
- Savings plans and other financial wellness tools
- Hybrid working opportunities
- Free breakfast, lunch, and snacks daily
- In-office wellness experiences and reimbursement
- Company-sponsored sports teams and fitness events
- Volunteer opportunities and charitable giving
- Social events, happy hours, treats, and celebrations
- Workshops and continuous learning opportunities
About the Company
- Tower Research Capital is a leading quantitative trading firm founded in 1998, built on a high-performance platform and independent trading teams with a 25+ year track record of innovation.
- Tower is home to world-class systematic trading and engineering talent, empowering portfolio managers independently while providing global organizational scale.
- Engineers develop electronic trading infrastructure, solving challenging problems in low-latency programming, FPGA technology, hardware acceleration, and machine learning.
- Ongoing investment in talent and technology ensures an unmatched platform in functionality, scalability, and performance.
- Business Support teams are essential to building and maintaining the platform, enabling trading and engineering teams to perform at their best.
- Employees find a stimulating, results-oriented environment with highly intelligent and motivated colleagues.
- Tower believes work should be both challenging and enjoyable, fostering a culture where smart, driven people thrive without egos.
- The open concept workplace, casual dress code, and well-stocked kitchens reflect a friendly, collaborative environment where everyone is respected and great ideas win.
- A collaborative and welcoming culture, a diverse team, and a workplace that values both performance and enjoyment, with no unnecessary hierarchy or ego.
Equal Opportunity
- Tower Research Capital is an equal opportunity employer.