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Nvidia Engineering Jobs in Georgia (NOW HIRING)

Contribute to GPU architecture decisions, kernel libraries, and internal performance-engineering best practices. What Were Looking For * Proven track record building NVIDIA CUDA kernels from ...

... g., NVIDIA Jetson platforms, SDRs) * Architect and optimize systems for embedded and HPC ... Collaborate cross-functionally with engineering, product, and business teams to deliver robust and ...

... g., NVIDIA Jetson platforms, SDRs) * Architect and optimize systems for embedded and HPC ... Collaborate cross-functionally with engineering, product, and business teams to deliver robust and ...

Service Engineer

Atlanta, GA · On-site

$70K - $100K/yr

... field engineering organization. Essential Duties and Responsibilities: Includes the following ... as NVIDIA HGX/DGX-based systems. • Troubleshoot GPU-related issues (ECC errors, thermal ...

AWS Architect

Atlanta, GA · On-site

$62.50 - $82/hr

... programming languages • Experience in using Scikit-learn, TensorFlow and/or Keras. • Knowledge / experience with Nvidia-docker, GPU specific technologies Please share your resumes to natraj.b ...

H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS ... What We Are Looking For * 5+ years in pre-sales, sales engineering, or solution architecture roles ...

Required : • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or ... Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc. • Live within ...

Senior Sales Engineer, Healthcare

Atlanta, GA · On-site

$100K - $138K/yr

H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS ... What We Are Looking For * 5+ years in pre-sales, sales engineering, or solution architecture roles ...

Cisco, Juniper, Arista, Nvidia HPE-Aruba, Palo Alto Networks, etc * Adept at using initiative ... Strong industry knowledge and operational empathy * 5+ yrs of pre-sales engineering or related ...

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Nvidia Engineering information

See Georgia salary details

$39.3K

$124K

$146.9K

How much do nvidia engineering jobs pay per year?

As of Jun 27, 2026, the average yearly pay for nvidia engineering in Georgia is $124,013.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,400.00 and $146,100.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior engineers in specialized fields such as software, hardware, or systems engineering at major technology companies can earn $500,000 or more annually, often including bonuses, stock options, and other compensation. Achieving this level typically requires extensive experience, advanced skills, and sometimes leadership roles or executive responsibilities.

What are the key skills and qualifications needed to thrive in the Nvidia Engineering position, and why are they important?

To thrive in Nvidia Engineering, candidates typically need strong proficiency in computer engineering, software development, and a solid understanding of hardware architecture, often backed by a relevant degree such as Electrical Engineering or Computer Science. Familiarity with tools like CUDA, C/C++, Python, and version control systems, as well as experience with GPU programming, are highly valued, and certifications such as Nvidia's Deep Learning Institute credentials can enhance a candidate's profile. Excellent problem-solving, team collaboration, and communication skills set top performers apart in this role. These skills and qualifications enable engineers to contribute effectively to complex, innovative projects that drive Nvidia's technological advancements.

What is an Nvidia Engineering job?

An Nvidia Engineering job involves designing, developing, and optimizing hardware or software solutions in areas such as graphics processing, AI, and high-performance computing. Engineers at Nvidia work on cutting-edge technologies, including GPUs, deep learning frameworks, and system architecture. Roles vary from hardware design and verification to software development and AI research, depending on expertise. Strong skills in programming, computer architecture, and problem-solving are typically required.

Which engineers does NVIDIA hire?

NVIDIA hires a variety of engineers including hardware engineers, software engineers, AI and deep learning engineers, and systems engineers. Candidates typically need strong technical skills, experience with programming languages like C++ and Python, and knowledge of GPU architectures or AI frameworks. The company values innovation, collaboration, and relevant technical certifications or degrees in engineering or computer science.

Is it hard to get hired at NVIDIA?

Getting hired as an engineer at NVIDIA can be competitive due to the company's reputation and high standards. Candidates typically need strong technical skills, relevant experience, and a solid understanding of areas like GPU architecture, software development, or AI. The hiring process often involves multiple interviews and technical assessments.

What types of projects do Nvidia Engineers typically work on, and how is teamwork structured within the engineering department?

Nvidia Engineers commonly engage in projects related to GPU development, AI and deep learning solutions, software driver optimization, and next-generation hardware innovation. Project teams are often multidisciplinary, bringing together software, hardware, and systems engineers to collaborate closely on end-to-end product development. Engineers frequently work in agile, fast-paced environments, attend regular team stand-ups, and participate in cross-functional meetings. This collaborative structure fosters creativity, accelerates problem-solving, and ensures high-quality product delivery while offering team members exposure to diverse technologies and career growth opportunities.

How much do NVIDIA engineers get paid?

NVIDIA engineers' salaries vary based on experience, role, and location, but the average annual salary for software engineers at NVIDIA typically ranges from $100,000 to $150,000. Senior engineers and those with specialized skills in AI, graphics, or hardware may earn higher compensation, often including bonuses and stock options.
What are the most commonly searched types of Nvidia Engineering jobs in Georgia? The most popular types of Nvidia Engineering jobs in Georgia are:
What are popular job titles related to Nvidia Engineering jobs in Georgia? For Nvidia Engineering jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Nvidia Engineering jobs in Georgia look for? The top searched job categories for Nvidia Engineering jobs in Georgia are:
What cities in Georgia are hiring for Nvidia Engineering jobs? Cities in Georgia with the most Nvidia Engineering job openings:
Infographic showing various Nvidia Engineering job openings in Georgia as of June 2026, with employment types broken down into 91% Full Time, and 9% Contract. Highlights an 83% In-person, 2% Hybrid, and 15% Remote job distribution, with an average salary of $124,013 per year, or $59.6 per hour.

CUDA Kernel Engineer

PRAGMATIKE

Atlanta, GA • Remote

Full-time

Medical, Dental, Vision, Retirement

Posted 24 days ago


Job description

Location: Remote US
Start date: ASAP
Languages: English (required)

About the Role

Pragmatike is hiring on behalf of a fast-growing AI startup recognized as a Top 10 GenAI company by GTM Capital, founded by MIT CSAIL researchers.

We are searching for a CUDA Kernel Engineer who has hands-on experience developing and optimizing NVIDIA CUDA kernels from scratch. You will work on the GPU performance layer powering large-scale, high-throughput AI systems used by Fortune 500 customers.

This role is ideal for someone who deeply understands NVIDIA GPU architecture, memory hierarchy, warp-level execution, and profiling workflowsnot someone coming from generic hardware, FPGA, or non-NVIDIA compute backgrounds. You will directly influence the GPU efficiency, throughput, and scalability of mission-critical AI systems.

What Youll Do

  • Design, implement, and optimize custom CUDA kernels for NVIDIA GPUs, with a focus on maximizing occupancy, memory throughput, and warp efficiency.
  • Profile GPU workloads using tools such as Nsight Compute, Nsight Systems, nvprof, and CUDA‐MEMCHECK.
  • Analyze and eliminate performance bottlenecks including warp divergence, uncoalesced memory access, register pressure, and PCIe transfer overhead.
  • Improve GPU memory pipelines (global, shared, L2, texture memory) and ensure proper memory coalescing.
  • Collaborate closely with AI systems, model acceleration, and backend distributed systems teams.
  • Contribute to GPU architecture decisions, kernel libraries, and internal performance-engineering best practices.

What Were Looking For

  • Proven track record building NVIDIA CUDA kernels from scratchnot just calling existing libraries.
  • Strong ability to optimize kernels (tiling strategies, occupancy tuning, shared memory design, warp scheduling).
  • Deep understanding of CUDA threads, warps, blocks, and grids, GPU memory hierarchy and memory coalescing, as well as warp divergence (how to detect, analyze, and mitigate it)
  • Experience diagnosing PCIe bottlenecks and optimizing host-device transfers (pinned memory, streams, batching, overlap).
  • Familiarity with C++, CUDA runtime APIs, and GPU debugging/profiling tooling.

Bonus Points

  • Experience with multi-GPU or distributed GPU systems (NCCL, NVLink, MIG).
  • Background in GPU acceleration for ML frameworks or HPC workloads.
  • Knowledge of model inference optimization (TensorRT, CUDA Graphs, CUTLASS).
  • Exposure to compiler-level optimization or PTX/SASS analysis.
  • Startup experience or comfort working in fast-moving, ambiguous environments.

Why This Role Will Pivot Your Career

  • Research pedigree: MIT CSAIL founders recognized for breakthrough AI and systems contributions.
  • Customer impact: Deploy AI solutions powering Fortune 500 clients.
  • Industry momentum: Lab alumni have led high-value acquisitions (MosaicML Databricks, Run:AI Nvidia, W&B CoreWeave).
  • Funding & growth: Oversubscribed seed round, next funding in 2026.
  • Career growth & influence: Lead AI initiatives, optimize pipelines, and directly impact production AI systems at scale.
  • Culture & autonomy: Own critical systems while collaborating with world-class engineers.
  • Aspirational impact: Solve GPU/AI performance challenges few engineers ever face.

Benefits

  • Competitive salary & equity options
  • Sign-on bonus
  • Health, Dental, and Vision
  • 401k

Pragmatike is an Equal Opportunity Employer and is committed to providing equal employment opportunities to all applicants without discrimination. We recruit on behalf of our clients and prohibit discrimination and harassment based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.We are committed to a fair and inclusive hiring process. We process your personal data solely for recruitment purposes, in accordance with applicable privacy laws, and maintain reasonable safeguards to protect your information. Your data may be shared with our client(s) for hiring consideration, but will not be disclosed to third parties outside of the recruitment process.