CUDA Developer

About the role

We are seeking a CUDA Developer with deep expertise in CUDA programming, GPU architecture, and high‑performance computing to design and optimize compute‑intensive workloads on modern accelerator hardware. This role focuses on extracting maximum performance from GPU platforms for AI training, inference, scientific computing, and high‑throughput data processing workloads. The developer will work closely with cross‑functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well‑engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers. Strong engineering discipline, clear communication, and a track record of shipping production‑ready work are essential.

Location: 100% Remote (U.S.)

Experience Required: 6+ years

Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H‑1B transfer candidates are encouraged to apply. We are unable to sponsor new H‑1B visa petitions for this position.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field
• Six or more years of experience in GPU programming and performance engineering
• Deep expertise in CUDA C/C++ and GPU programming models
• Strong understanding of modern GPU architectures, memory hierarchies, and execution models
• Hands‑on experience profiling and optimizing GPU workloads in production
• Familiarity with NCCL, MPI, and high‑performance interconnect technologies
• Experience integrating custom kernels into ML frameworks
• Strong C++ skills and familiarity with modern systems programming practices
• Solid grounding in linear algebra and numerical methods
• Strong communication and collaboration skills with research and engineering teams

Preferred Qualifications

• Experience with Triton, CUTLASS, or other GPU kernel authoring frameworks
• Familiarity with TensorRT, FasterTransformer, or vLLM internals
• Exposure to compiler infrastructure such as LLVM or MLIR
• Open‑source contributions to GPU or ML performance libraries
• Experience with large‑scale distributed training infrastructure

Pay

Salary Range: $85,000–$110,000 annually.

Schedule

Full‑time, Direct W2.