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Phd Software Engineer Jobs in Raleigh, NC (NOW HIRING)

Computer Futures

Software Engineer 1

Raleigh, NC · On-site

Graduated with or in the final months of obtaining a PhD degree in Electrical engineering with major in power systems, in a US-Based University Qualifications 3.5+ GPA Excellent understanding of ...

Broadcom

R&D SW Engineer

Durham, NC

PhD in a related technical field with 3+ years of relevant software development experience Legal ... Coach and mentor junior engineers; support onboarding and knowledge transfer * Work closely with ...

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Phd Software Engineer information

See Raleigh, NC salary details

$61.7K

$143.4K

$199.8K

How much do phd software engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for phd software engineer in Raleigh, NC is $143,405.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,600.00 and $168,200.00 per year, depending on experience, location, and employer.

What is a PhD software engineer?

A PhD Software Engineer is a professional who has completed a Doctor of Philosophy (PhD) degree specializing in computer science, software engineering, or a related field, and works in designing, developing, and optimizing software systems. They often engage in advanced research, develop innovative algorithms, and solve complex technical problems. Their expertise is typically utilized in roles that require deep technical knowledge, research skills, and the ability to push the boundaries of current technology. PhD Software Engineers are commonly found in academia, research institutions, and leading technology companies.

What does a PhD software engineer do?

As a PhD Software Engineer, you are often entrusted with tackling complex problems and leading research-driven projects that require advanced analytical and technical skills. Your daily work may involve designing novel algorithms, conducting experiments, and collaborating closely with cross-functional teams such as data scientists and product managers. Additionally, you might mentor junior engineers and help shape the technical direction of your team. This role leverages your research background to bridge the gap between academic innovation and practical software solutions.

What are the key skills and qualifications needed to thrive as a PhD software engineer?

A PhD Software Engineer requires advanced programming expertise, strong analytical and research skills, and typically a doctorate in computer science or a related field. Familiarity with specialized programming languages, version control systems like Git, and experience with research-oriented software tools are common technical requirements. Exceptional problem-solving, collaboration, and communication skills help bridge the gap between research and practical application. These abilities are crucial for driving innovation, translating complex theories into scalable solutions, and contributing to cutting-edge technology projects.

What are popular job titles related to Phd Software Engineer jobs in Raleigh, NC?

For Phd Software Engineer jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Phd Software Engineer jobs in Raleigh, NC look for?

The top searched job categories for Phd Software Engineer jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Phd Software Engineer jobs?

Cities near Raleigh, NC with the most Phd Software Engineer job openings:

Phd Software Engineer jobs near you
Infographic showing various Phd Software Engineer job openings in Raleigh, NC as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 9% Part Time, and 4% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $143,405 per year, or $68.9 per hour.

Senior Software Engineer - GPU Local AI Platforms

Nvidia

Durham, NC

$118K - $156K/yr

Full-time

Posted 29 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 246 rated software companies

Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology-and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

NVIDIA's Local AI team is building the software stack that makes large language models and generative AI applications run at maximum efficiency on NVIDIA edge AI hardware. The AI ecosystem moves fast; our job is to make sure end users get the best experience. We own the platform - performance, CI/CD pipelines, validated recipes, and model bring-up infrastructure - that lets developers run groundbreaking LLMs out of the box. The open-source community builds fast; our platform is what turns community innovation into something developers and partners can rely on at scale.

What you'll be doing:

  • Track and evaluate innovations in leading open-source LLM inference frameworks - identify performance-critical features and algorithmic improvements relevant to NVIDIA edge AI hardware

  • Analyze how new model architectures and inference algorithms (attention variants, MoE routing, speculative decoding, multi-token prediction, quantized inference) map onto NVIDIA GPU architecture - identify mismatch, fallback paths, and optimization opportunities

  • Characterize multi-node inference behavior: collective communication primitives (NCCL/RCCL), topology-aware all-reduce strategies, and parallelism efficiency on edge cluster configurations

  • Produce performance analysis reports mapping theoretical hardware limits (memory bandwidth, FLOP/s, interconnect throughput) to observed inference throughput, latency, and utilization

  • Own the model validation workflow for new model releases: architecture compatibility assessment, inference recipe development, performance characterization, and publication to developer recipe sites

  • Develop and maintain developer-facing inference recipes: keep them accurate as frameworks evolve, automate staleness detection, and build feedback loops from CI results to recipe updates

  • Engage with community and partners on model bring-up questions; serve as the technical point of contact for hardware-specific inference issues related to partner concerns

What we need to see:

  • BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.

  • 12+ years of software engineering with depth in GPU computing, ML systems, or high-performance inference

  • Strong Python or C++ programming, software design, and software engineering skills.

  • Hands-on experience with GPU kernel development or optimization (CUDA/C++, Triton, or equivalent) - you understand how thread blocks, memory hierarchy, and warp execution affect real-world performance

  • Working knowledge of LLM inference internals: attention mechanisms, KV-cache management, continuous batching, quantization formats, and tensor parallelism

  • Container engineering expertise: multi-architecture Docker or OCI builds, layer optimization, runtime configuration, NVIDIA Container Toolkit

  • Strong analytical skills: ability to form a performance hypothesis, design an experiment, interpret results, and communicate findings clearly

Widely considered to be one of the technology world's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 28, 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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