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Remote Intel Physics Jobs (NOW HIRING)

IonQ

Senior Field Engineer - US Federal

$192K - $252K/yr

Inspire and co-engineer solutions with the US Intel Agencies by explaining IonQ's strategy ... as Chemistry, Physics or Engineering * Motivated learner with a strong interest in quantum ...

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Sufficient Physics, Mathematics, and /or Engineering course work covering basic electromagnetics ...

The Pennsylvania State University

$96K - $114K/yr

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Modeling and simulation, particularly to resolve questions of interacting systems, applied physics ...

Rohde & Schwarz

Account Manager - DoW Test Ranges

$150K - $200K/yr

... Remote Your tasks * Grow Rohde & Schwarz market share - develop and manage sales funnel/forecast as ... Physics) and/or 5+ years of hands-on mission execution in either Spectrum Management, EW or Intel ...

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Remote Intel Physics information

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How much do remote intel physics jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for remote intel physics in the United States is $20.06, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $25.48 per hour, depending on experience, location, and employer.

What is a remote intel physics?

A Remote Intel Physics job involves working with physics-based data analysis, modeling, and interpretation to support intelligence operations, all while working from a remote location. Professionals in this field apply their expertise in physics to solve complex problems related to surveillance, reconnaissance, and national security. They may analyze sensor data, develop simulation models, or interpret technical information to provide insights for defense or intelligence agencies. Strong analytical skills, proficiency with scientific software, and security clearance are often required.

What are the key skills and qualifications needed to thrive as a remote intel physics specialist?

To thrive as a Remote Intel Physics Specialist, you need a strong background in physics, data analysis, and intelligence methodologies, typically supported by an advanced degree in physics or a related field. Familiarity with data modeling tools, remote sensing technologies, and classified information systems is often required. Analytical thinking, attention to detail, and strong communication skills are important soft skills for interpreting data and collaborating with multidisciplinary teams. These skills are essential for producing actionable intelligence and supporting mission-critical decision-making in secure, remote environments.

What are some common challenges faced by professionals in remote intel physics positions, and how can they be addressed?

Professionals in Remote Intel Physics roles often encounter challenges such as managing sensitive data securely while collaborating with distributed teams, and staying updated with rapidly evolving analytical tools and methodologies. Effective communication across time zones and maintaining data integrity are also key concerns. To address these, it's important to utilize secure collaboration platforms, participate in regular virtual meetings, and engage in continuous professional development. Building strong relationships with team members and setting clear protocols for data handling can help mitigate these challenges and ensure efficient workflow.

What is the difference between Remote Intel Physics vs Remote Data Scientist?

AspectRemote Intel PhysicsRemote Data Scientist
Required CredentialsPhysics degree, specialized physics certificationsStatistics, computer science, or data analytics degrees
Work EnvironmentResearch labs, government agencies, tech companiesTech firms, finance, healthcare, consulting
Industry UsageDefense, aerospace, scientific researchBusiness analytics, AI, machine learning
Common Search IntentPhysics research, scientific modelingData analysis, predictive modeling

Remote Intel Physics and Remote Data Scientist roles both require analytical skills but differ in focus. Intel Physics emphasizes physics knowledge and scientific research, while Data Scientists focus on data analysis and machine learning. Both roles are in high demand in tech and research sectors, often offering remote opportunities.

Does Intel hire physicists?

Yes, Intel hires physicists for roles related to research and development, materials science, and semiconductor physics. These positions often require strong analytical skills, knowledge of quantum mechanics, and experience with tools like microscopy and simulation software.
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Remote Intel Physics jobs near you
Infographic showing various Remote Intel Physics job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 79% Physical, 2% Hybrid, and 19% Remote job distribution, with an average salary of $41,731 per year, or $20.1 per hour.

Senior GPU Performance Software Engineer

Intel

Hillsboro, OR • On-site, Remote

$195K - $275K/yr

Full-time

Medical, Retirement, PTO

Posted 12 days ago

Intel rating

8.7

Company rating: 8.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

18th of 161 rated electronics manufacturers

Job description

Job Details:Job Description: 

About the Role

The Software and AI (SAI) organization is seeking a highly skilled software engineer to contribute to the development and low-level optimization ofoneDNN, a complex, cross-platform, open-source performance library that serves as the foundation for deep learning applications (github.com/uxlfoundation/oneDNN).
Please Note:This is a low-level software engineering and hardware-acceleration role. It does not involve building, training, or tuning machine learning models. Instead, you will focus on developing highly optimized math primitives, parallel algorithms, and GPU kernels that power industry-leading AI frameworks (such as OpenVINO, TensorFlow, PyTorch, and ONNX Runtime) on Intel hardware.
Key Responsibilities
Kernel Development and Architecture
  • Develop high-performance GEMM, convolution, and attention kernels for AI workloads
  • Design scalable JIT and codegen infrastructure for GPU kernel generation
Low-Level Optimization
  • Implement fusion and memory-traffic optimizations to maximize hardware utilization
  • Optimize mixed-precision and quantized execution paths (e.g., BF16, FP16, INT8, FP8, FP4, etc.)
Performance Modeling and Profiling
  • Build analytical and empirical performance models for kernel dispatch and tuning
  • Profile and eliminate performance bottlenecks across oneDNN GPU primitives and runtime paths
Hardware and Software Co-Design
  • Co-design GPU primitives and kernel architectures for next-generation Intel GPUs
  • Partner with hardware and compiler teams to shape future accelerator capabilities and software stacks
Infrastructure and Validation
  • Improve validation, benchmarking, and CI infrastructure for performance-critical GPU workloads
Why Join Us
Massive Scale
  • Work on a global, high-impact open-source library that scales AI performance across millions of devices worldwide
Cutting-Edge Hardware
  • Get early access to and influence the software stack for Intel's roadmap of next-generation discrete GPUs
Expert Collaboration
  • Work alongside industry-leading experts in GPU compilers, hardware architecture, and performance libraries
Total Rewards
  • Enjoy a competitive package including stock programs, quarterly bonuses, robust healthcare, and highly flexible hybrid/remote working options
What We're Looking For
To be successful in this role, you should demonstrate the following professional traits:
  • A strong ownership mindset - you take initiative on complex, ambiguous technical problems and drive them to resolution
  • A collaborative approach - you work effectively across hardware, compiler, and framework teams to align on shared technical goals
  • A performance-driven curiosity - you are motivated by squeezing every cycle out of hardware and continuously seek deeper understanding of low-level systems
Qualifications:
Minimum Qualifications
  • Education:BSc, MSc, or PhD in Computer Science, Computer Engineering, Mathematics, Physics, or a highly technical related field
  • Core Language:5+ years of professional software development experience with expert-level modern C++
  • Performance Optimizations:2+ years of hands-on experience in programming and kernel optimization on GPUs (via SYCL/DPC++, OpenCL, CUDA, or HIP), or at least 5+ years of similar low-level performance optimization experience on CPUs
  • Hardware Architecture:Strong foundations in computer architecture, cache hierarchies, memory subsystems, and parallel programming paradigms (e.g., multi-threading, SIMD/vectorization)
Preferred Qualifications
  • Math Libraries:Experience developing high-performance math libraries (e.g., GEMM, convolution, reduction, or FFT kernels)
  • Low-Level Tuning:Hands-on experience with GPU assembly-level tuning or compiler optimization
  • Parallel APIs:Familiarity with parallel programming APIs such as OpenMP or oneTBB
  • AI Workload Context:Basic understanding of deep learning primitives (e.g., forward/backward passes) to understand how library code is utilized by upstream frameworks
Job Type:Experienced HireShift:Shift 1 (United States of America)Primary Location: US, Oregon, HillsboroAdditional Locations:US, California, Santa ClaraPosting Statement:All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.Position of TrustN/ABenefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.

Annual Salary Range for jobs which could be performed in the US: $195,200.00-275,580.00 USDThe range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.

Work Model for this Role

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.

*

ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.

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About Intel

Sourced by ZipRecruiter

Intel strives to make every facet of semiconductor manufacturing state-of-the-art -- from semiconductor process development and manufacturing, through yield improvement to packaging, final test and optimization, and world class Supply Chain and facilities support. Employees in the Technology and Manufacturing Group are part of a worldwide network of design, development, manufacturing, and assembly/test facilities, all focused on utilizing the power of Moore's Law to bring smart, connected devices to every person on Earth

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1968

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