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Internship Deep Reinforcement Learning Jobs in Oregon

Agility Robotics

Staff AI Research Engineer

Salem, OR · On-site +1

$216K - $338K/yr

Develop core reinforcement learning infrastructure, including scalable training pipelines and ... Strong programming skills in Python, with proficiency in deep learning frameworks such as PyTorch.

Agility Robotics

Staff AI Research Engineer

Salem, OR · On-site

$216K - $338K/yr

Develop core reinforcement learning infrastructure, including scalable training pipelines and ... Strong programming skills in Python, with proficiency in deep learning frameworks such as PyTorch.

Netflix

OR

$466K - $750K/yr

... models, deep learning, search and recommender systems, causal inference, reinforcement learning and bandits, computer vision, computer graphics, natural language processing, and computational ...

Agility Robotics

Senior AI Research Engineer

Salem, OR · On-site +1

$195K - $304K/yr

Develop core reinforcement learning infrastructure, including scalable training pipelines and ... Strong programming skills in Python, with proficiency in deep learning frameworks such as PyTorch.

Agility Robotics

Senior AI Research Engineer

Salem, OR · On-site

$195K - $304K/yr

Develop core reinforcement learning infrastructure, including scalable training pipelines and ... Strong programming skills in Python, with proficiency in deep learning frameworks such as PyTorch.

Fuze Health

OR

Deep experience in NLP, LLMs, Generative AI, and/or Reinforcement Learning. * Experience in healthcare, pharmaceuticals, supply chain, or logistics optimization. * Expertise in building and ...

Intel

Sr. Machine Learning Engineer

Hillsboro, OR · On-site

$113K - $156K/yr

... reinforcement learning. * Ability to own and drive a research agenda independently, generating ... internship experiences and or schoolwork/classes/research. Benefits at Intel Our total rewards ...

Varsity Tutors

Artificial Intelligence (AI) Tutor

OR · Remote

$18 - $40/hr

Deep knowledge of machine learning algorithms, neural networks, natural language processing, computer vision, reinforcement learning, search algorithms, knowledge representation, probabilistic ...

LP Careers Page

OR · Hybrid

Hands-on experience across core technique areas: multi-armed bandit / reinforcement learning ... LLMs / deep learning applied to personalization or content * Familiarity with Looker TOTAL ...

LP Careers Page

OR · Hybrid

Hands-on experience across core technique areas: multi-armed bandit / reinforcement learning ... LLMs / deep learning applied to personalization or content * Familiarity with Looker TOTAL ...

LP Careers Page

OR · Hybrid

Hands-on experience across core technique areas: multi-armed bandit / reinforcement learning ... LLMs / deep learning applied to personalization or content * Familiarity with Looker TOTAL ...

LP Careers Page

OR · Hybrid

Hands-on experience across core technique areas: multi-armed bandit / reinforcement learning ... LLMs / deep learning applied to personalization or content * Familiarity with Looker TOTAL ...

Aptive

You bring both deep technical rigor and the communication skills needed to translate complex AI ... Apply supervised, unsupervised, and reinforcement learning techniques to develop and evaluate data ...

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Internship Deep Reinforcement Learning information

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.

What are popular job titles related to Internship Deep Reinforcement Learning jobs in Oregon? For Internship Deep Reinforcement Learning jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Internship Deep Reinforcement Learning jobs in Oregon look for? The top searched job categories for Internship Deep Reinforcement Learning jobs in Oregon are:
What cities in Oregon are hiring for Internship Deep Reinforcement Learning jobs? Cities in Oregon with the most Internship Deep Reinforcement Learning job openings:
Internship Deep Reinforcement Learning jobs near you

Senior AI Software Engineer, Reinforcement Learning

Agility Robotics

Salem, OR

$187K - $292K/yr

Full-time

Posted 10 days ago

Job description

Agility's commercially deployed humanoids operate alongside teams in warehouses, manufacturing facilities, and distribution centers—tackling physically demanding and repetitive tasks while enabling workers to focus on higher-value work. With industry-leading safety standards and years of proven deployment data, we're pioneering a new era of automation that enhances human potential.

Agility is a pioneer. Our robot, Digit, is the first to be sold into workplaces across the globe. Our team is differentiated by its expertise in imagining, engineering, and delivering robots with advanced mobility, dexterity, intelligence, and efficiency -- robots specifically designed to work alongside people, in spaces built for people. Every day, we break through engineering challenges and invent new solutions and capabilities that will one day make robots commonplace and approachable. This work is our passion and our responsibility: our mission is to make businesses more productive and people's lives more fulfilling.

Why Join Now

Digit is one of the only humanoid robots deployed in real customer facilities today—at Schaeffler, GXO, Toyota Motor Manufacturing Canada, and Mercado Libre, with 65,000+ hours of real-world operation logged. In June 2026 we announced plans to become the first pure-play humanoid robotics company to trade publicly (ticker AGLT), in a ~$2.5B merger backed by NVIDIA, Amazon, SoftBank Vision Fund 2, and Foxconn. With $300M+ in orders for Digit and a factory built for 10,000 robots a year, we're scaling fast—and the policies you build will ship to robots working alongside people in production, not sit in simulation.

About the Role

The AI Controls team builds high-rate learned controllers that let Digit move robustly, efficiently, and safely in dynamic environments. As an AI Controls Engineer, you'll develop and deploy reinforcement learning policies across humanoid locomotion, whole-body control, and manipulation—integrating perception to enable collision-free, perceptive motion in the real world.

About The Work

  • Design, train, and deploy robust RL policies for locomotion, manipulation, whole body control, and dynamic interactions with the environment.
  • Integrate perception into RL policies to achieve obstacle-aware, collision-free motion, and perceptive manipulation.
  • Develop and maintain core RL infrastructure, including scalable training pipelines and evaluation frameworks.
  • Design and implement new simulation environments and tasks to support training and evaluation of control policies.
  • Collaborate with on-robot software and deployment teams to ship production-quality policies to Digit.

About You

  • 4+ years of experience developing and deploying RL policies for robotics applications.
  • Strong Python skills and hands-on experience with a deep learning framework such as PyTorch.
  • Experience designing reward functions, tuning hyperparameters, and implementing exploration strategies to solve complex control tasks.
  • Experience with perception-in-the-loop control, integrating real-time sensory inputs for reactive or adaptive behaviors.
  • Proven experience deploying reinforcement learning policies on real-world bipedal or quadrupedal robots.
  • Familiarity with robot simulation environments (e.g. Mujoco-Warp, Isaac) and sim-to-real transfer.
  • A collaborative approach and the ability to deliver safe, high-quality software in a fast-paced environment.

Bonus Qualifications

  • Advanced degree (MS or PhD) in Robotics, Computer Science, or a related field.
  • Experience with contact-rich manipulation, including force-torque or tactile sensing.
  • Familiarity with policy distillation (e.g. teacher–student) for transferring state-based policies to perception-driven ones.
  • Publications in top ML or robotics conferences (e.g. NeurIPS, ICML, CoRL, RSS, ICRA).

This a hybrid position based out of one of our Salem, Pittsburgh, or Fremont offices.

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.

Anticipated Salary Range
$187,000—$292,000 USD

In addition to base pay, our competitive total rewards package consists of the following for full-time employees:

  • 401(k) Plan: Includes a 6% company match.
  • Equity: Company stock options.
  • Insurance Coverage: 100% company-paid medical, dental, vision, and short/long-term disability insurance for employees.
  • Benefit Start Date: Eligible for benefits on your first day of employment.
  • Well-Being Support: Employee Assistance Program (EAP).
  • Time Off:
    • Exempt Employees: Flexible, unlimited PTO and 12 company holidays, including a winter shutdown.
    • Non-Exempt Employees: 10 vacation days, paid sick leave, and 12 company holidays, including a winter shutdown, annually.
  • On-Site Perks: Catered lunches four times a week and a variety of healthy snacks and refreshments at our Salem and Pittsburgh locations.
  • Parental Leave: Generous paid parental leave programs.
  • Work Environment: A culture that supports flexible work arrangements.
  • Growth Opportunities: Professional development and tuition reimbursement programs.
  • Relocation Assistance: Provided for eligible roles.
  • Annual Discretionary Bonus: Provided for eligible roles.

All of our roles are U.S.-based. Applicants must have current authorization to work in the United States.

Agility Robotics is committed to a work environment in which all individuals are treated with respect and dignity. Each individual has the right to work in a professional atmosphere that promotes equal employment opportunities and prohibits unlawful discriminatory practices, including harassment. Therefore, it is the policy of Agility Robotics to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, age, disability, marital status, citizenship, national origin, genetic information, or any other characteristic protected by law. Agility Robotics prohibits any such discrimination or harassment.

Agility Robotics does not accept unsolicited referrals from third-party recruiting agencies. We prioritize direct applicants and encourage all qualified candidates to apply directly through our careers page. If you are represented by a third party, your application may not be considered. To ensure full consideration, please apply directly.