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Internship Deep Reinforcement Learning Jobs in Portland, OR

Intel

AI Performance Library Architect

Hillsboro, OR

$170K - $315K/yr

... years+ Machine learning and deep learning algorithms or High-performance computing (HPC ... internship experiences and/or schoolwork/classes/research. Job Type:Experienced Hire Shift:Shift 1 ...

Jobs for Humanity

Speakers/Writers

Vancouver, WA

$15 - $60/hr

Utilize your deep understanding of the field to identify potential biases, limitations, or ... Interest in AI and machine learning concepts. Important Information This is a freelance position ...

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How much do internship deep reinforcement learning jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for internship deep reinforcement learning in Portland, OR is $18.07, according to ZipRecruiter salary data. Most workers in this role earn between $15.29 and $20.38 per hour, depending on experience, location, and employer.

What types of projects or tasks can I expect to work on during a deep reinforcement learning internship?

As a Deep Reinforcement Learning (DRL) intern, you'll typically work on projects involving the development, implementation, and evaluation of reinforcement learning algorithms. This might include tasks like training agents in simulated environments, tuning hyperparameters, analyzing performance metrics, and collaborating with team members to integrate DRL solutions into larger systems. You'll also likely spend time reading recent research papers, experimenting with frameworks such as TensorFlow or PyTorch, and presenting your findings to the research team. Collaboration with mentors and other interns is common, and you'll gain hands-on experience that prepares you for more advanced roles in AI research or engineering.

What is an internship in deep reinforcement learning?

An internship in Deep Reinforcement Learning (DRL) is a temporary, hands-on position where interns learn and apply state-of-the-art machine learning algorithms that enable computers to learn decision-making tasks through trial and error. Interns typically work on projects involving neural networks, reward systems, and environments like games or simulations. These internships provide valuable experience with frameworks such as TensorFlow or PyTorch, and exposure to current research in artificial intelligence. The experience helps students or recent graduates build technical skills and prepare for careers in AI research or industry.

What are the key skills and qualifications needed to thrive as an intern in deep reinforcement learning?

To thrive as an Intern in Deep Reinforcement Learning, you need a solid background in mathematics (especially linear algebra, probability, and calculus), programming (Python), and foundational knowledge in machine learning principles, usually supported by ongoing or completed coursework in computer science or related fields. Familiarity with frameworks and tools such as TensorFlow, PyTorch, OpenAI Gym, and experience using version control systems like Git are typically required. Analytical thinking, curiosity, and effective communication are essential soft skills for collaborating on research problems and sharing complex findings. These skills and qualities are crucial for contributing to innovative projects and successfully navigating the challenges of cutting-edge AI research.

What is the difference between Internship Deep Reinforcement Learning vs Data Science Intern?

AspectInternship Deep Reinforcement LearningData Science Intern
Required SkillsMachine learning, programming (Python), reinforcement learning conceptsStatistics, data analysis, programming (Python/R), data visualization
Work EnvironmentResearch labs, AI companies, tech startupsBusiness analytics, tech firms, consulting agencies
Industry UsageAI research, robotics, autonomous systemsBusiness intelligence, marketing, finance

Internship Deep Reinforcement Learning focuses on developing algorithms that enable systems to learn through trial and error, often in AI research or robotics. Data Science Internships involve analyzing data to extract insights and support decision-making. While both roles require programming skills, reinforcement learning emphasizes AI-specific techniques, whereas data science centers on statistical analysis and data visualization.

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Internship Deep Reinforcement Learning jobs near you

AI Performance Library Architect

Intel Corporation

Hillsboro, OR • On-site

$170K - $315K/yr

Full-time

Medical, Retirement, PTO

Re-posted 16 days ago

Intel rating

8.7

Company rating: 8.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

19th of 156 rated electronics manufacturers

Job description

Job Details:
Job Description:
Software and AI (SAI) organization is looking for a software development engineer to work on oneDNN project ( https://github.com/uxlfoundation/oneDNN ). oneDNN is a complex cross-platform open-source software project focusing on neural network performance. oneDNN is a critical and highly visible component of Intel AI strategy, powering key AI applications including OpenVINO, Tensorflow, Pytorch, ONNX Runtime, and more. In this role, you will be responsible for design, development, and maintenance of new functionality in oneDNN to enable performance critical portions of AI workloads. In this role you will be supporting software developers optimizing AI frameworks and workloads for Intel CPUs and GPUs, as well as cross-platform ecosystem of AI software developers contributing to oneDNN.
Qualifications:
You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the requirements and are considered a plus factor in identifying top candidates.
Minimum requirements:
  • Master's degree in Mathematics, Physics, Computer Science, or a relevant STEM field. OR
  • Ph.D. degree in Mathematics, Physics, Computer Science, or a relevant STEM field.
  • 5+ years of experience in the following areas:
    • C and C++
    • Maintaining or contributing to open-source software projects
    • Software libraries design and architecture
    • Implementation of linear algebra algorithms (functions from BLAS, LAPACK, or PyTorch)
    • Performance engineering and software performance optimizations
    • Floating point arithmetic and numerical stability
    • Software development on Linux
    • Low-level performance optimizations using CUDA, x86 assembly or intrinsics, or OpenCL

Preferred qualifications:
  • 3 years+ Machine learning and deep learning algorithms or High-performance computing (HPC) applications development
  • 3 year+ Floating point implementations of transcendental functions (sin, cos, tanh, elu, etc)
  • 1 year+ Algorithms for non-IEEE low precision data types (bfloat16, fp8, fp4)
  • 1 year+ AI assisted software development

Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and/or schoolwork/classes/research.
Job Type:
Experienced Hire
Shift:
Shift 1 (United States of America)
Primary Location:
US, Oregon, Hillsboro
Additional Locations:
US, California, Folsom
Business group:
The Software Team drives customer value by enabling differentiated experiences through leadership AI technologies and foundational software stacks, products, and services. The group is responsible for developing the holistic strategy for client and data center software in collaboration with OSVs, ISVs, developers, partners and OEMs. The group delivers specialized NPU IP to enable the AI PC and GPU IP to support all of Intel's market segments. The group also has HW and SW engineering experts responsible for delivering IP, SOCs, runtimes, and platforms to support the CPU and GPU/accelerator roadmap, inclusive of integrated and discrete graphics.
Posting 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 Trust
N/A
Benefits
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: $170,500.00-315,490.00 USD
The 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

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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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