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Reinforcement Learning Engineer Jobs in Oregon (NOW HIRING)

Intel

Sr. Machine Learning Engineer

Hillsboro, OR

$113K - $156K/yr

... reinforcement learning. * Ability to own and drive a research agenda independently, generating ... Research-engineering balance: Ability to produce production-quality implementations of novel ...

Agility Robotics

Staff AI Research Engineer

Salem, OR · On-site +1

$216K - $338K/yr

Mentor and guide junior AI research engineers through project design, experiment execution, and ... Develop core reinforcement learning infrastructure, including scalable training pipelines and ...

Agility Robotics

Staff AI Research Engineer

Salem, OR

$216K - $338K/yr

Mentor and guide junior AI research engineers through project design, experiment execution, and ... Develop core reinforcement learning infrastructure, including scalable training pipelines and ...

Fuze Health

OR

... reinforcement learning to improve prescription and fulfillment workflows. * Identify and prioritize high-impact opportunities for ML and automation, collaborating with product, engineering, and ...

Agility Robotics

Senior AI Research Engineer

Salem, OR

$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 +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.

Netflix

OR

$466K - $750K/yr

... reinforcement learning Links: Netflix Research site Our long term business view NOTE: This job posting is inclusive of a variety of positions within our AI for Member Systems (AIMS) Engineering group.

Netflix

OR · On-site

$466K - $750K/yr

Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models Evidence Personalization Page Simulation for Better Offline Metrics at Netflix RecSysOps As a software engineer ...

LP Careers Page

OR · Hybrid

Hands-on experience across core technique areas: multi-armed bandit / reinforcement learning ... Collaborative: Leans on ML engineering for the last mile rather than working solo * Coachable:

LP Careers Page

OR · Hybrid

Hands-on experience across core technique areas: multi-armed bandit / reinforcement learning ... Collaborative: Leans on ML engineering for the last mile rather than working solo * Coachable:

Natera

Staff Machine Learning Scientist, Agentic AI

OR · On-site +1

... of-Thought, alongside reinforcement fine-tuning (RFT) to ensure agents provide accurate ... Establish production-grade machine learning engineering standards and reproducible architectures ...

LP Careers Page

OR · Hybrid

Hands-on experience across core technique areas: multi-armed bandit / reinforcement learning ... Collaborative: Leans on ML engineering for the last mile rather than working solo * Coachable:

LP Careers Page

OR · Hybrid

Hands-on experience across core technique areas: multi-armed bandit / reinforcement learning ... Collaborative: Leans on ML engineering for the last mile rather than working solo * Coachable:

Agility Robotics

Senior Manager, AI Innovation

Salem, OR · On-site +1

$268K - $364K/yr

... reinforcement learning, and large language models (LLMs) applied to robotics. * Proven track record of managing scaling high-performance engineering or research teams. * Experience deploying models ...

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All JobsReinforcement Learning Engineer JobsReinforcement Learning Engineer Jobs in Oregon

Reinforcement Learning Engineer information

See Oregon salary details

$40.2K

$122.5K

$202.5K

How much do reinforcement learning engineer jobs pay per year?

As of Aug 1, 2026, the average yearly pay for reinforcement learning engineer in Oregon is $122,502.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,800.00 and $160,200.00 per year, depending on experience, location, and employer.

What are Reinforcement Learning Engineers?

Reinforcement Learning Engineers are specialized professionals who design, develop, and implement algorithms based on reinforcement learning, a type of machine learning where agents learn to make decisions by receiving rewards or penalties. They work on building models that enable machines to learn optimal actions through trial and error in complex environments. Their responsibilities often include developing RL architectures, tuning hyperparameters, running simulations, and applying RL methods to real-world problems like robotics, gaming, or recommendation systems. RL Engineers typically have strong backgrounds in computer science, mathematics, and deep learning, along with experience in programming languages like Python and frameworks such as TensorFlow or PyTorch.

What are the key skills and qualifications needed to thrive as a Reinforcement Learning Engineer, and why are they important?

To thrive as a Reinforcement Learning Engineer, you need a strong background in machine learning, mathematics (especially probability and statistics), and programming languages like Python, often supported by a relevant degree in computer science or engineering. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), RL libraries (like OpenAI Gym), and cloud computing platforms is typically required. Problem-solving skills, creativity, and effective collaboration help set outstanding engineers apart in this field. These competencies enable the design and deployment of advanced RL solutions that address real-world challenges and drive innovation.

What are some common challenges faced by Reinforcement Learning Engineers when deploying models in real-world environments?

One of the main challenges Reinforcement Learning (RL) Engineers face is bridging the gap between simulation and real-world deployment. Models that perform well in controlled environments may struggle with unpredictable data, safety constraints, or limited feedback in production. Additionally, RL algorithms often require significant computational resources and careful tuning to avoid instability. Collaboration with domain experts and software engineers is essential to address these issues and ensure successful integration of RL solutions into existing systems.

What is the difference between Reinforcement Learning Engineer vs Machine Learning Engineer?

AspectReinforcement Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's in CS, AI, or related; experience with RL frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on RL applicationsTech companies, data-driven firms, AI departments across industries
Industry UsageSpecialized in RL projects like robotics, game AI, autonomous systemsBroader applications including predictive modeling, NLP, computer vision

Reinforcement Learning Engineers focus on developing algorithms that learn through interactions with environments, often in robotics or gaming. Machine Learning Engineers work on a wider range of models and applications. While both roles require strong programming and math skills, RL Engineers specialize in sequential decision-making, whereas ML Engineers handle diverse data-driven tasks across industries.

What are popular job titles related to Reinforcement Learning Engineer jobs in Oregon? For Reinforcement Learning Engineer jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Engineer jobs in Oregon look for? The top searched job categories for Reinforcement Learning Engineer jobs in Oregon are:
What cities in Oregon are hiring for Reinforcement Learning Engineer jobs? Cities in Oregon with the most Reinforcement Learning Engineer job openings:
Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Oregon as of July 2026, with employment types broken down into 74% Full Time, and 26% Contract. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $122,502 per year, or $58.9 per hour.

Sr. Machine Learning Engineer

Intel

Hillsboro, OR

$113K - $156K/yr

Full-time

Medical, Retirement, PTO

Posted 7 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: 
Job Description
Our Mission

At Intel, our journey is to transform AI into something safer, more trustworthy, and respectful of human privacy by design. We believe transformative AI should have a positive impact on people-powerful in capability, yet honest about its limits and protective of the data and resources it touches.

To get there, we build agentic AI that combines the best of local and cloud intelligence - private, affordable, and sustainable by design. Small, efficient models run directly on the user's machine (AI PC, edge, on-prem, and beyond), keeping data private and token costs low, while powerful cloud models handle the hardest work: planning, reasoning, and complex problem-solving. Today, neither approach can deliver this alone. Together, they give people real capability without compromise-data stays private, spend stays predictable, and energy use stays in check.

We're building intelligence that scales without sacrificing trust, cost, or the planet-because the future of AI should belong to the people it serves

Role Summary

We are seeking a **Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal candidate designs and implements algorithms for agent harness and post-training pipelines, develops RL environments and reward models, and conducts training runs to improve model capabilities for agentic applications.

What you'll do

Work in a dynamic team to:

  • Build evaluation benchmarks and metrics

  • Build and iterate on agent harness, including context engineering, agent memory, tools, skills.

  • Build, maintain, and iterate on the post-training pipeline: Develop robust, reproducible training workflows from data ingestion and preprocessing through model checkpointing and deployment

  • Design RL environments and reward functions - Develop environments, reward signals, and verifiable reward frameworks for training models on reasoning-intensive tasks.

  • Debug and optimize training runs - Profile training jobs, resolve bottlenecks, improve GPU utilization, and address numerical instability at multi-GPU scale

What you'll learn / grow into

Curiosity is required. You will develop:

  • How post-training techniques actually move model performance

  • How to make small models punch above their weight as agent backends

  • How model choices interact with runtime constraints on edge hardware

IMPORTANT:

Please be informed that Intel is proactively trying

to find candidates for this position which is frequently available

at Intel.

Please note that the position may not be available

at this time. If you would be interested in this position should it

become available, we would encourage you to apply, and our

hiring team will be glad to contact you when/if relevant.

Qualifications:
Qualifications

Minimum qualifications are required to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
You must possess the minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.

Required Qualifications

  • BS in CS, EE, Math or related STEM field

  • 8+ years software development background

  • 4+ years of hands-on experience in machine learning engineering, data science or ML research.

  • Experiences designing and building evaluation frameworks and benchmarks that accurately measure model capability improvements and alignment quality

  • Proficient in Python

  • Proficient in LLM architectures, optimization and model training dynamics.

Preferred Qualifications

  • Masters or PhD degrees are preferred.

  • 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 agenda independently, generating hypotheses and prioritizing experiments without step-by-step supervision.

  • Ambiguity tolerance: Comfortable making progress in fast-moving environments where problem definitions evolve and priorities shift.

  • Debug-first mindset: Willingness and skill to dive deeply into large, complex ML codebases to isolate and fix subtle issues.

  • Research-engineering balance: Ability to produce production-quality implementations of novel research ideas, balancing rigor with speed.

  • Collaborative work style: Comfort with cross-functional collaboration.

  • Clear technical communication: Ability to explain research results, architectural decisions, and trade-offs to both technical and non-technical stakeholders.

  • Ability to learn new technologies fast and adapt to changes with open-mindedness.

Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.

Benefits at Intel

Our total rewards package goes above and beyond just a paycheck. Whether you're looking to build your career, improve your health, or protect your wealth, we offer generous benefits to help you achieve your goals. Go to Intel Benefits | Intel Careers for details of benefits available to you. Intel reserves the right to modify, change or discontinue benefit plans at any time in its sole discretion.

#LDI

Job Type:Shift:Shift 1 (United States of America)Primary Location: US, California, Santa ClaraAdditional Locations:US, Arizona, Phoenix, US, California, Folsom, US, Oregon, HillsboroPosting 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: $195,200.00-361,200.00 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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