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Senior DevTech Compute Engineer, Compression and Data Processing

Pay
Multiple pay amounts — pay source
#LI-Hybrid Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 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.
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Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Prototype and integrate GPU-accelerated compression and data processing methods

  • Analyze and optimize complex data-intensive workloads on GPU/CPU systems

  • Influence next-generation hardware, software and programming models with NVIDIA teams

  • Integrate solutions with the largest NVIDIA customers and cloud providers

From the employer’s posting
you will prototype and integrate novel approaches to GPU-accelerated distributed data processing domains
perform in-depth analysis and optimization of complex data intensive workloads
Influence the design of next-generation hardware architectures, software, and programming models
Work directly with the NVIDIA largest customers and CSPs to integrate the solutions
Education & alternatives
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.
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.
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Posting record

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Status in our records
Live
First seen by us
Aug 18, 202686 days ago
Recorded sightings
177
Last seen by us
Nov 11, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$127K–$190K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 2,239 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 86

Up longer than most. Similar jobs usually come down between day 6 and day 55.

Well past Nvidia’s usual: its jobs come down by about day 39.

From 13,214 similar postings that came down, and 100 of Nvidia’s. Coming down is not always a hire.

Nvidia is hiring

104 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Engineer hiring is picking up
  • Takes jobs down at a usual pace
Hiring record

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Where the posting names them
- 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

Your next step

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About Nvidia

People
About 42,000 in 2026, up 17% from the year before.Annual report (SEC Form 10-K)
Company
Listed as NVDA.
H-1B visas
978 approved for new hires in fiscal 2025.US Citizenship and Immigration Services

Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 860, the most 1,354, and the latest week had 1,335.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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 other objective job-related factors. The expected base salary ranges for this position are:
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 November 3, 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.

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Pay
#LI-Hybrid Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 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.
Location & working pattern

US, CA, Santa Clara

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 other objective job-related factors. The expected base salary ranges for this position are: 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
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