Senior DevTech Compute Engineer, Compression and Data Processing

NVIDIA Corporation; Santa Clara (CA); Hybrid; USD 184,000 - 357,000; Full time

Job summary

NVIDIA Corporation in Santa Clara, CA seeks a Senior DevTech Compute Engineer for Compression and Data Processing to prototype and integrate GPU-accelerated methods for dataframe analytics, high-throughput compression, and distributed databases. You will work with research, hardware, software libraries, and tools teams to optimize data-intensive workloads.

Required: Masters or PhD in CS/CE/Applied Math and 5+ years of experience, plus hands-on CUDA/ROCm/Metal and parallel programming expertise,

Qualifications

• Masters or PhD in Computer Science, Computer Engineering, Applied Math and/or related computationally focused science degree (or equivalent experience).
• At least 5+ years of relevant work or research experience, with a track record in state-of-the-art systems or complex projects.

Responsibilities

• Prototype and integrate novel approaches to GPU-accelerated distributed data processing domains: dataframe analytics, high-throughput lossless/lossy compression methods, transactional and vector databases.
• Collaborate with research, hardware, system software, libraries, and tools teams to optimize data-intensive workloads and influence design of future architectures.

Skills

CUDA

ROCm

Metal

OpenMP

MPI

pthreads

TBB

C/C++

Education

Master's or PhD in Computer Science/Computer Engineering/Applied Math

Tools

ROCm

CUDA Toolkit

OpenACC

Job description

NVIDIA is currently seeking a highly motivated Senior DevTech Compute Engineer for Compression and Data Processing! Would you enjoy prototyping and developing ground breaking methods and data formats to accelerate complex distributed workflows? Do you love investigating and overcoming system-level bottlenecks for multi-stage and multi-IP overlapped workloads? Do you prefer squeezing all useful entropy out of data, whether it is columnar row-groups, DL tensors or multidimensional images and videos? Are you excited about co-designing the systems, software components and hardware blocks to define the next frontier for distributed data processing? If so, this is an outstanding opportunity for you to join the Developer Technology Compute team. Data analytics, databases and distributed data processing is one of the fastest growing domains for non-CPU accelerated computing: “on-the-wire” compression and decompression is already part of the switches and DPUs, low-latency queries across huge amounts of data in data lakes at scale in the middle of the RL training run defines the business agility. Here at NVIDIA Devtech Compute team we take a holistic approach to data movement, late materialization, memory management and spilling, parallel algorithms, collectives and compression and quantization. Read more from the team: Designing GPU Query Engines, Cut Checkpoints Costs or take a look at some of the projects in depth: NVIDIA nvCOMP, NVIDIA GPU Query Engine (GQE), NVIDIA cuCollections.

What you will be doing:

In this role, you will prototype and integrate novel approaches to GPU-accelerated distributed data processing domains: dataframe analytics, high-throughput low-latency advanced lossless and lossy compression methods, transactional and vector databases. Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex data intensive workloads to ensure the best possible performance of current heterogeneous GPU/CPU architectures. Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA. Work directly with the NVIDIA largest customers and CSPs to integrate the solutions at Speed-Of-Light, and influence open standards in data analytics and compression

What we need to see:

• Masters or PhD in Computer Science, Computer Engineering, Applied Math and/or related computationally focused science degree (or equivalent experience).
• At least 5+ years of relevant work or research experience, with a track record in the state-of-the-art systems or complex projects, involving cross-team collaboration and solid prioritization skills.
• Hands-on experience with low-level parallel programming across execution units (CPU/GPU/NPU/ASICs), e.g., CUDA, ROCm, Metal, OpenACC, OpenMP, MPI, pthreads, TBB, etc.
• Fluency in C/C++, algorithms and data structures CPU/GPU/NPU accelerators architecture fundamentals, memory subsystem, caches, NICs and storage I/O Domain expertise in data processing, compression and decompression, codecs or in high performance distributed databases, ETL and data analytics.

Ways to stand out from the crowd:

• PhD or a recent project/publication in a relevant field.
• Background in compression (lossless/lossy, ANS, Bitpack), video or image codecs (H.264, H.265, AV1, ProRes), low-latency data analysis, storage systems, networking, and distributed computer architectures.
• Track of records in zero-to-one project or initiatives, spanning several stakeholders and resulting in substantial TCO gains or enabling new workflows.
• Open-source contributions or committee participation in the related domain and fields.
• Excellent interpersonal skills, problem solving, and the ability to communicate efficiently in sophisticated technical scenarios

NVIDIA is recognized as one of the most desirable employers. We’re honored that Glassdoor has named our founder and CEO, Jensen Huang, No. 1 on its 2026 Best CEOs list. In addition, we have some of the most forward-thinking and hardworking people in the world working here. If you're ambitious, creative, and autonomous, come join us and contribute to a team that is pushing the edges of what can be done in AI. #LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until August 21, 2026. This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA.