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Tower Research Capital

Software Engineer, GPU Fleet

New York$200k–$300kmidAdded 2 days ago

About this role

Tower Research Capital seeks a Software Engineer to build and maintain the operational infrastructure for its GPU fleet, handling management, monitoring, and troubleshooting across hardware and software layers. You'll automate fleet operations, collaborate with engineering teams to improve efficiency, and solve complex performance issues in a fast-growing infrastructure critical to the firm's quantitative trading platform.

What you'll do

  • Build and maintain automation tooling for GPU fleet operations including management, monitoring, metrics collection, and network configuration
  • Troubleshoot software and hardware issues across the fleet from application layer down to kernel and operating system
  • Work with engineering teams to tune workloads and optimize GPU utilization and efficiency
  • Analyze GPU job statistics to identify trends, inefficiencies, and improvement opportunities
  • Manage GPU hardware deployment, configuration, and performance tuning across diverse equipment

What they're looking for

  • Python development
  • GPU management and troubleshooting
  • Linux/UNIX system administration
  • Debugging and root cause analysis
  • Configuration management and monitoring tools
  • Hardware tuning and optimization
  • CI/CD tools and processes
  • Computer science fundamentals and software design

Benefits

  • Generous paid time off policies
  • Hybrid working opportunities
  • Free breakfast, lunch, and snacks daily
  • In-office wellness experiences and reimbursement for gym and personal training
  • Company-sponsored sports teams and fitness events
  • Workshops and continuous learning opportunities
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Tower Research Capital

Tower Research Capital builds high-performance quantitative trading systems and infrastructure, serving traders and researchers with low-latency platforms for market data, strategy execution, and order management. The company is hiring software engineers, quantitative developers, and infrastructure specialists to design scalable systems, optimize trading platforms, and enhance development tooling.

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Likely interview questions

  • Walk us through a time you debugged a complex hardware or driver issue—what tools and methodology did you use?
  • Describe your experience deploying and managing GPU infrastructure at scale. What challenges did you encounter?
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