Remote C++/CUDA Developer for Low-Latency HPC

Eqvilent; United States; Remote; USD 120,000 - 170,000; Full time

Benefits offered by this job

Work remotely from anywhere in the世界

Job summary

Eqvilent is seeking a Software Developer with commercial experience in low- and ultra-low latency GPU/CPU projects to join our dynamic team. You will implement complex algorithms and refactor existing solutions to improve scalability, with a strong focus on latency and throughput.

The ideal candidate is curious, detail-oriented, and comfortable working in remote or hybrid teams, while staying current with GPU/HPC/ML trends.

Qualifications

• Commercial experience in developing and debugging high-performance GPU and CPU applications with strong focus on latency and throughput.
• Hands-on experience with third-party libraries and designing custom CUDA kernels.
• Proficient with profiling and performance analysis tools (Nsight Systems, Nsight Compute, nvprof).
• Solid understanding of data structures, algorithms, and object-oriented programming in C++.
• Proven ability to work effectively in remote or hybrid teams with project-based responsibilities.
• Curiosity and proactive engagement with emerging trends in GPU/HPC/ML, continuously seeking to learn and apply new techniques.

Responsibilities

• Implementation of complex computational algorithms on GPU and CPU with demanding latency and throughput requirements.
• Refactor existing solutions to improve their scalability.

Skills

C++

Latency-focused development

GPU/CPU development

Profiling & optimisation

Remote/hybrid collaboration

Tools

Nsight Systems

Nsight Compute

nvprof

CUDA kernels

Job description

Eqvilent is seeking a Software Developer with commercial experience in low- and ultra-low latency GPU/CPU projects to join our dynamic team. You will implement complex algorithms and refactor existing solutions to improve scalability, with a strong focus on latency and throughput.

The ideal candidate is curious, detail-oriented, and comfortable working in remote or hybrid teams, while staying current with GPU/HPC/ML trends.