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Applied Research Scientist Jobs (NOW HIRING)

RESEARCH SCIENTIST 2 , Plasma Science and Fusion Center (PSFC) , to conduct fundamental and applied research in the areas of Disruptions, MagnetoHydroDynamics (MHD) stability and control, and Machine ...

Senior Research Scientist We are seeking a highly skilled Senior Research Scientist with a strong technical background and proven expertise in machine learning and artificial intelligence. As the AI ...

Senior Research Scientist We are seeking a highly skilled Senior Research Scientist with a strong technical background and proven expertise in machine learning and artificial intelligence. As the AI ...

Senior Research Scientist We are seeking a highly skilled Senior Research Scientist with a strong technical background and proven expertise in machine learning and artificial intelligence. As the AI ...

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Applied Research Scientist information

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$50.5K

$130.1K

$174K

How much do applied research scientist jobs pay per year?

As of Sep 15, 2026, the average yearly pay for applied research scientist in the United States is $130,117.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What is an applied research scientist?

Applied Research Scientists are professionals who use scientific methods and research techniques to solve real-world problems, often focusing on practical applications rather than theoretical understanding. They typically work in industries like technology, healthcare, or engineering, where they develop new products, improve processes, or innovate solutions. Their work involves designing experiments, analyzing data, and collaborating with cross-functional teams to bring research findings into practical use. Applied Research Scientists often bridge the gap between fundamental research and product development, ensuring that scientific advancements translate into tangible benefits.

What are some common challenges faced by applied research scientists when transitioning projects from research to practical application?

Applied Research Scientists often encounter challenges in bridging the gap between theoretical research and real-world implementation. Translating complex findings into scalable, user-friendly solutions requires close collaboration with engineering, product, and business teams. Balancing rigorous scientific standards with practical constraints like timelines, budgets, and stakeholder expectations is crucial. Effective communication and adaptability are key, as projects may need to be iteratively refined based on feedback from diverse teams.

What are the key skills and qualifications needed to thrive as an applied research scientist, and why are they important?

To thrive as an Applied Research Scientist, you typically need an advanced degree (Master’s or PhD) in a relevant scientific field, strong analytical skills, and experience with experimental design and data analysis. Familiarity with programming languages (such as Python or R), statistical software, and machine learning frameworks is essential, and certifications in data science or specialized research methodologies can be advantageous. Excellent problem-solving, communication, and collaboration skills set outstanding candidates apart, enabling them to translate research findings into practical solutions. These competencies are crucial for driving innovation, effectively communicating results, and advancing organizational goals through impactful scientific research.

What is the difference between Applied Research Scientist vs Data Scientist?

AspectApplied Research ScientistData Scientist
CredentialsTypically requires a PhD or master's in a related fieldUsually holds a bachelor's or master's in data science, statistics, or related fields
Work EnvironmentFocuses on developing new algorithms, models, and scientific researchAnalyzes data to extract insights, build predictive models, and support decision-making
Industry UsageCommon in tech, academia, and R&D divisions of companiesWidely used across industries like finance, healthcare, and marketing

Applied Research Scientists focus on creating innovative algorithms and scientific advancements, often in research settings, while Data Scientists analyze data to solve business problems. Both roles require strong technical skills, but their primary goals and work environments differ.

Are applied research scientists paid well?

Applied research scientists typically earn competitive salaries that vary by industry, experience, and location. They often hold advanced degrees and possess specialized skills in data analysis, machine learning, or engineering, which can contribute to higher compensation levels compared to other research roles.
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What are popular job titles related to Applied Research Scientist jobs?

For Applied Research Scientist jobs, the most frequently searched job titles are:

Infographic showing various Applied Research Scientist job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 87% Full Time, 10% Part Time, and 1% Contract. Highlights an 76% Physical, 4% Hybrid, and 20% Remote job distribution, with an average salary of $130,117 per year, or $62.6 per hour.

Senior Quantum AI Research Scientist, Applied Research

Santa Clara, CA • Hybrid

Nvidia
Computer and Electronic Product Manufacturing • 10K+ employees

$115K - $147K/yr

Full-time

Re-posted 26 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz


Job description

At NVIDIA, we're solving the world's most exciting problems with our unique approach to accelerated computing. We're looking for a passionate AI research scientist with deep quantum computing expertise to path-find the future of fault-tolerant quantum systems powered by machine learning.

Quantum computing is a strategic priority for NVIDIA, and our goal is to accelerate the entire ecosystem. As a Sr. Applied Research Scientist in Quantum Computing, you will architect and build AI solutions at the heart of fault-tolerant quantum computing-spanning quantum error correction, decoding, calibration, and beyond. You will research and develop open AI models, curated datasets, and rigorous benchmarks that advance the state of the art and empower the broader quantum community. Your research will help translate cutting-edge theory into practice by fine-tuning models for specific quantum error-correcting codes and hardware platforms, while collaborating with multi-functional teams across Product, Engineering, and Applied Research to integrate AI into next-generation Accelerated Quantum Supercomputers!

Do you love developing new technology, enjoy working with collaborative people and teams around the world, and operating at the speed of light? If yes, we would love to hear from you!

What you'll be doing:

  • Design and architect AI/ML models-including deep neural networks, graph neural networks, transformers, and reinforcement-learning agents-for quantum error correction, syndrome decoding, logical operation synthesis, and real-time calibration in fault-tolerant quantum systems.

  • Develop cutting-edge AI techniques for quantum computing that contribute to NVIDIA's open model efforts across the quantum ecosystem.

  • Help create high-quality, large-scale datasets for quantum error correction and quantum system characterization, including simulated and hardware-derived syndrome data, enabling the community to train and evaluate AI models at scale.

  • Collaborate with quantum hardware teams to collect and structure hardware-derived training data, enabling domain-adapted models that improve over time as hardware matures.

  • Co-design AI solutions with quantum hardware and software teams, ensuring decoders and calibration models meet latency and throughput requirements for real-time operation inside fault-tolerant feedback loops.

  • Communicate research findings through top-tier venues and collaborate with academic and industry partners to advance the field, while championing a culture of rapid innovation, technical depth, and creative problem solving.

What we need to see:

  • Degree in Computer Science, Physics, Applied Mathematics, Electrical Engineering, or a related field (Ph.D. strongly preferred); equivalent demonstrated experience also considered.

  • 8+ years of combined experience in quantum computing and/or AI/ML research, with a track record of high-impact contributions in at least one of these domains.

  • Deep expertise in machine learning and deep learning-including model architecture design, training at scale, and evaluation-applied to scientific or engineering problems.

  • Strong background in Quantum Information Science, including quantum error correction, fault-tolerant protocols, and quantum noise models.

  • Excellent communication skills and the ability to collaborate effectively with multi-functional teams across research, engineering, and product.

Ways to stand out from the crowd:

  • Hands-on experience developing learned decoders or AI-driven calibration systems for quantum hardware (superconducting qubits, trapped ions, or other platforms).

  • Experience with large-scale model training and fine-tuning-including parameter-efficient fine-tuning (LoRA, QLoRA, adapters) and domain adaptation for scientific AI models.

  • Proficiency with CUDA and NVIDIA GPU programming for accelerating quantum simulation, AI model training, or real-time decoding workloads.

  • Experience with high-performance computing (HPC) environments and distributed training frameworks (e.g., PyTorch Distributed, Megatron-LM, or JAX pmap) for large-scale quantum AI workloads.

  • Passion to drive AI innovations into NVIDIA software and hardware products that support the broader quantum computing ecosystem.

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/

#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 192,000 USD - 304,750 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 25, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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

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Hours and flexibility

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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