GPU Software Engineer (CUDA)

About This Opportunity

Our talent team is representing a confidential technology consulting organization seeking a GPU Software Engineer (CUDA) for a 100% remote position within the United States. This is a direct-hire, full-time W2 role with an established firm delivering cloud, AI, and enterprise solutions.

We are looking for engineers with 7+ years of experience who bring deep expertise in CUDA programming, GPU architecture, and high-performance computing. You'll design and optimize compute-intensive workloads on modern accelerator hardware, focusing on AI training, inference, scientific computing, and high-throughput data processing.

Responsibilities

• Design and optimize GPU-accelerated workloads for AI, scientific computing, and data processing applications
• Develop high-performance CUDA C/C++ kernels and extract maximum performance from modern GPU platforms
• Profile and optimize GPU workloads in production environments to deliver measurable performance improvements
• Integrate custom kernels into machine learning frameworks and collaborate with ML infrastructure teams
• Work with cross-functional partners including product, design, engineering, operations, and business stakeholders to translate requirements into engineered solutions
• Conduct code reviews and design reviews while mentoring junior engineers
• Collaborate with research and engineering teams on distributed training infrastructure and high-performance computing initiatives

What We're Looking For

Required:

• Bachelor's or Master's degree in Computer Science, Computer Engineering, or related field
• 6+ 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 modern systems programming practices
• Solid grounding in linear algebra and numerical methods
• Strong communication and collaboration skills
• U.S. work authorization (U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates; no new H-1B sponsorship available)

Preferred:

• 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

How We Work With You

When you apply through Get A Job.ai, a recruiter from our team will review your profile and conduct an initial screening. If there's a strong match, we'll submit your candidacy to our client for consideration. Please do not contact the client directly—all communication flows through our recruiting team to ensure a professional and coordinated process.

Pay

Pay via Get A Job.ai: $80,000–$107,000 annually

Equal Employment Opportunity

Get A Job.ai is committed to equal employment opportunity for all candidates regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.