Job Details

Job Summary We are seeking a GPU Systems Engineer with deep expertise in CUDA programming, GPU architecture, and high-performance computing to design and optimize compute-intensive workloads on modern accelerator hardware. The role focuses on extracting maximum performance from GPU platforms for AI training, inference, scientific computing, and high-throughput data processing workloads. The ideal candidate combines low-level systems mastery with strong software engineering practices and has a track record of delivering measurable performance improvements on production GPU systems. The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production.Key Responsibilities Design and implement high-performance CUDA kernels for compute-intensive workloads across AI and HPC use casesProfile and optimize GPU code using tools such as Nsight Systems, Nsight Compute, and CUDA profilersTune memory access patterns, occupancy, register usage, and shared memory utilization for peak performanceDevelop highly optimized libraries for linear algebra, attention, and other ML primitivesOptimize multi-GPU and multi-node training using NCCL, RDMA, and high-performance networkingImplement custom operators and fused kernels in PyTorch, JAX, or TritonCollaborate with ML engineers to identify performance bottlenecks in training and inference pipelinesDevelop benchmarks and regression tests to safeguard performance over timeEvaluate new GPU architectures and feature sets, and advise on adoption strategyContribute to compiler-level optimizations for tensor programs where appropriate, working at the boundary between ML frameworks and underlying accelerator codegen to unlock performance not reachable through framework-level tuning aloneOptimize memory hierarchy usage across HBM, L2, shared memory, and registersImplement mixed-precision and quantized compute paths that maximize accelerator throughput while preserving numerical fidelity within bounds acceptable for the target workloadsDocument performance characteristics, design decisions, and tuning playbooks for internal teamsStay current with GPU architecture, CUDA evolution, and emerging accelerator technologiesRequired Qualifications Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related fieldSix or more years of experience in GPU programming and performance engineeringDeep expertise in CUDA C/C++ and GPU programming modelsStrong understanding of modern GPU architectures, memory hierarchies, and execution modelsHands-on experience profiling and optimizing GPU workloads in productionFamiliarity with NCCL, MPI, and high-performance interconnect technologiesExperience integrating custom kernels into ML frameworksStrong C++ skills and familiarity with modern systems programming practicesSolid grounding in linear algebra and numerical methodsStrong communication and collaboration skills with research and engineering teamsPreferred Qualifications Experience with Triton, CUTLASS, or other GPU kernel authoring frameworksFamiliarity with TensorRT, FasterTransformer, or vLLM internalsExposure to compiler infrastructure such as LLVM or MLIROpen-source contributions to GPU or ML performance librariesExperience with large-scale distributed training infrastructureHow to Apply For immediate consideration, please send your resume to harry@bvteck.com or contact us at (908) 676-4399. Learn more about Bright Vision Technologies at www.bvteck.com.Equal Employment Opportunity Bright Vision Technologies is an Equal Opportunity Employer, including Disability/Veterans. We recognize that our people are our strength, and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.#J-18808-Ljbffr