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Senior Reinforcement Learning Jobs in Oregon (NOW HIRING)

Agility Robotics

Senior AI Research Engineer

Salem, OR · On-site +1

$195K - $304K/yr

Develop core reinforcement learning infrastructure, including scalable training pipelines and evaluation frameworks. * Design and implement new simulation environments and tasks to support training ...

Agility Robotics

Senior AI Research Engineer

Salem, OR · On-site

$195K - $304K/yr

Develop core reinforcement learning infrastructure, including scalable training pipelines and evaluation frameworks. * Design and implement new simulation environments and tasks to support training ...

Intel

Sr. Machine Learning Engineer

Hillsboro, OR · On-site

$113K - $156K/yr

Hands-on experience implementing and scaling the full **post-training pipeline** for language models including supervised fine tuning and reinforcement learning. * Ability to own and drive a research ...

Agility Robotics

Senior Manager, AI Innovation

Salem, OR · On-site +1

$268K - $364K/yr

About The Role The Senior Manager of AI Innovation will be a key leader within our cutting-edge ... Strong expertise in core AI domains, including computer vision, reinforcement learning, and large ...

Care Access

Senior Trainer, Clinical Education

OR · On-site +1

The Senior Trainer, Clinical Education will play a key role in delivering, standardizing, and ... and reinforcement of learning. * Develop, review, and maintain documentation, training templates ...

Slalom Consulting

General Information

Portland, OR · On-site

Slalom Flex (Project Based) - Senior Change Manager Location: Portland, OR *Please note: This role ... Resistance Management & Reinforcement • Identify sources of resistance and develop tailored ...

SOLV Energy

Senior SCADA Engineer, Design (Remote)

OR · On-site +1

$104K - $143K/yr

Perform senior-level review of SCADA drawing sets and generate redlines at standard revision ... reinforcement of design standardswhilefosteringa culture of continuous learning and engineering ...

Infiltrator Water Technologies

EH&S Manager

Sutherlin, OR

$81K - $110K/yr

Reporting to the Sr. EHS Manager, this role collaborates with cross-functional leaders to foster a ... Drive near-miss reporting, learning, and closure of corrective actions. * Facilitate and monitor ...

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Senior Reinforcement Learning information

What does a senior reinforcement learning engineer do?

A Senior Reinforcement Learning Engineer designs, develops, and implements advanced machine learning algorithms that enable systems to learn optimal behaviors through trial and error. They work on complex problems such as robotics, game AI, recommendation systems, and automated decision-making. In addition to coding and model development, they often lead research initiatives, collaborate with cross-functional teams, and mentor junior engineers. Their role requires deep knowledge of reinforcement learning theory, practical experience with machine learning frameworks, and strong programming skills.

What are some common challenges faced by senior reinforcement learning professionals when deploying models in real-world environments?

Senior Reinforcement Learning professionals often encounter challenges such as ensuring model robustness when transferring algorithms from simulated to real-world environments, handling limited or noisy data, and managing the computational demands of training complex models. Additionally, safety and interpretability are critical, as real-world deployments can have significant impacts if models behave unpredictably. Close collaboration with domain experts and engineering teams is essential to address these challenges and ensure successful, scalable deployments.

What are the key skills and qualifications needed to thrive as a senior reinforcement learning engineer, and why are they important?

To thrive as a Senior Reinforcement Learning Engineer, you need deep expertise in machine learning, reinforcement learning algorithms, and programming languages such as Python, often supported by an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and RL-specific libraries, as well as experience with high-performance computing and cloud platforms, is typically required. Strong problem-solving abilities, collaboration, and communication skills help distinguish top performers in this role. These skills ensure the development of efficient, robust RL models and effective teamwork on complex AI projects.

What is the difference between Senior Reinforcement Learning vs Data Scientist?

AspectSenior Reinforcement LearningData Scientist
Required CredentialsAdvanced degrees in CS, ML, or related fields; experience with RL frameworksDegree in CS, Statistics, or related; strong analytical skills
Work EnvironmentResearch labs, AI teams, tech companies focusing on ML projectsBusiness analytics, data analysis, and modeling in various industries
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, marketing, tech, and more

While both roles require strong analytical skills and technical knowledge, Senior Reinforcement Learning specialists focus on developing RL algorithms and models, often in AI research settings. Data Scientists analyze data to inform business decisions across industries. The roles overlap in data handling and programming but differ in their core focus and application areas.

What are the most commonly searched types of Reinforcement Learning jobs in Oregon?

The most popular types of Reinforcement Learning jobs in Oregon are:

What are popular job titles related to Senior Reinforcement Learning jobs in Oregon?

For Senior Reinforcement Learning jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Senior Reinforcement Learning jobs in Oregon look for?

The top searched job categories for Senior Reinforcement Learning jobs in Oregon are:

What cities in Oregon are hiring for Senior Reinforcement Learning jobs?

Cities in Oregon with the most Senior Reinforcement Learning job openings:

Senior Reinforcement Learning jobs near you

Senior AI Software Engineer, Reinforcement Learning

Agility Robotics

Salem, OR • On-site

$187K - $292K/yr

Full-time

Posted 24 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.