Remote- Systems Engineering -

GPU Systems Engineer - Remote
is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. Job Title: GPU Systems Engineer

Location: 100% Remote (U.Position Type: Full-time, Direct W2

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.

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. This 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. In this role you 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. 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.

Design and implement high-performance CUDA kernels for compute-intensive workloads across AI and HPC use cases.

Tune memory access patterns, occupancy, register usage, and shared memory utilization for peak performance.

Optimize multi-GPU and multi-node training using NCCL, RDMA, and high-performance networking.

Collaborate with ML engineers to identify performance bottlenecks in training and inference pipelines.

Develop benchmarks and regression tests to safeguard performance over time.

Contribute 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 alone.

Implement mixed-precision and quantized compute paths that maximize accelerator throughput while preserving numerical fidelity within bounds acceptable for the target workloads.

Document performance characteristics, design decisions, and tuning playbooks for internal teams.

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.

Familiarity with NCCL, MPI, and high-performance interconnect technologies.

Strong C++ skills and familiarity with modern systems programming practices.

Strong communication and collaboration skills with research and engineering teams.

Open-source contributions to GPU or ML performance libraries.

Experience with large-scale distributed training infrastructure.

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.