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

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 variable, project-based responsibilities
Curiosity and proactive engagement with emerging trends in GPU/HPC/ML, continuously seeking to learn and apply new techniques
In-depth knowledge and expertise in low-latency and real-time development, achieving sub-microsecond latency
Experience with lock-free data structures and associated design patterns
Proficient in C programming, including writing Linux drivers and working with kernel-level components
Strong understanding of Linux system internals and networking
Knowledge of memory optimization techniques (shared memory, registers, coalesced access, persistent kernels)
Experience with inference optimization frameworks

C++/CUDA Developer

Key skills