NVIDIA Logo

NVIDIA

Senior DevTech Compute Engineer, Compression and Data Processing

Posted 13 Days Ago
In-Office or Remote
2 Locations
184K-357K Annually
Senior level
In-Office or Remote
2 Locations
184K-357K Annually
Senior level
Prototype and integrate GPU-accelerated distributed data processing, compression, databases, and analytics solutions. Optimize complex data-intensive workloads across heterogeneous CPU/GPU architectures, collaborate on next-generation hardware and software designs, and work with customers and cloud service providers to deploy solutions and influence open standards. The role requires deep expertise in parallel programming, C/C++, accelerator architecture, memory systems, and compression or distributed data systems.
The summary above was generated by AI

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.

Similar Jobs

28 Minutes Ago
In-Office or Remote
United States
Entry level
Entry level
Greentech • Hardware • Internet of Things • Machine Learning • Software • Business Intelligence • Agriculture
Halter is building a talent pool for people considering returning to New Zealand, Australia, or joining the USA team. Opportunities may span software, digital product, firmware, data, systems, machine learning, hardware, production, trades, supply chain, sales, field support, customer success, research, marketing, strategy, operations, and people teams. Applicants should submit a CV or LinkedIn profile, current and preferred location, anticipated relocation timing, and relevant visa or partner employment information.
Yesterday
Easy Apply
Remote
United States
Easy Apply
175K-195K Annually
Senior level
175K-195K Annually
Senior level
Healthtech • Software
Leads and develops a Data Platform engineering team while owning delivery of complex data initiatives. The role establishes delivery discipline, assesses technical and implementation risks, partners cross-functionally, and drives production reliability, data quality, observability, incident management, and on-call readiness. It also guides the evolution of scalable data ingestion, transformation, lakehouse, cloud architecture, governance, and reusable platform capabilities.
Top Skills: Amazon AthenaApache AirflowApache IcebergSparkAWSAws GlueCi/CdEtl/EltPysparkS3
Yesterday
Easy Apply
Remote or Hybrid
United States
Easy Apply
119K-180K Annually
Senior level
119K-180K Annually
Senior level
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.
Top Skills: ClaudeDatabricksDbtPythonSQLStreamlitTableau

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account