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Reinforcement Learning Engineer Jobs in Oregon (NOW HIRING)

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 ...

NVIDIA is seeking an experienced Principal EDA R&D Engineer to pioneer the next generation of ... Reinforcement Learning, and Graph Neural Networks) that autonomously analyze RTL topologies ...

New

NVIDIA is seeking an experienced Principal EDA R&D Engineer to pioneer the next generation of ... Reinforcement Learning, and Graph Neural Networks) that autonomously analyze RTL topologies ...

New

NVIDIA is seeking an experienced Principal EDA R&D Engineer to pioneer the next generation of ... Design, develop, and deploy multi-agent AI systems (using LLMs, Reinforcement Learning, and Graph ...

New

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:

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:

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:

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:

This role combines hands-on software engineering with applied research in generative methods, and ... Experience generating data for agentic, tool-use, or reinforcement-learning post-training. NVIDIA ...

Senior Software Architect, AI Systems and Networking

OR · On-site +1

$129K - $175K/yr

Background of Reinforcement Learning systems. With competitive salaries and a comprehensive ... If you are a senior data engineer passionate about building largescale, highimpact data platforms ...

Physical AI Solutions Architect

Hillsboro, OR

$68.50 - $90.50/hr

Minimum Qualifications - Bachelor's degree in Computer Science, Engineering, Robotics, AI, or ... action (VLA) models, reinforcement learning, imitation learning, and sim-to-real workflows ...

Showing results 21-40

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 Sep 13, 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 is a reinforcement learning engineer?

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 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 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 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 cities in Oregon are hiring for Reinforcement Learning Engineer jobs?

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

Infographic showing various Reinforcement Learning Engineer job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $122,502 per year, or $58.9 per hour.

Principal Research Scientist, Synthetic Data Generation

OR • On-site, Remote

Nvidia
Computer and Electronic Product Manufacturing • 10K+ employees

Full-time

Posted 7 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz


Job description

NVIDIA is at the forefront of the AI revolution, and our research is shaping the future of large language models. We are looking for a Principal Scientist to set the technical direction for synthetic data generation across NVIDIA's frontier model efforts. You will define and build open-source libraries within the NVIDIA NeMo ecosystem that generate synthetic datasets across text, code, structured, and multimodal data, feeding the pre- and post-training of LLMs such as Nemotron.

This role combines hands-on software engineering with applied research in generative methods, and you will collaborate with research, engineering, product, and model teams as well as external labs. What you'll be doing: Build and scale data generation pipelines using LLM-based methods combined with automated quality evaluation. resulting in datasets to improve both initial training and fine-tuning of LLMs such as Nemotron.

These data pipelines cover reasoning, coding, structured output, and multimodal understanding. Pioneer data generation for agentic and tool-use training: synthetic trajectories, multi-turn interactions, function calling, and executable environments for reinforcement learning, including reward modeling and verifiable-reward data Advance multimodal synthetic data generation - image, document, video, and audio - in partnership with NVIDIA's model teams. Advance privacy-preserving and safe synthesis - differential privacy, anonymization, and de-identification - enabling model training on sensitive data in regulated domains.

Develop and maintain open-source libraries and SDKs with clean APIs and strong documentation. Drive software excellence with modern tooling, architecture based on configuration, and professional Git/CI-CD. Publish original research at top machine learning and AI conferences to maintain NVIDIA's technical leadership.

Mentor scientists and engineers across the team, raising the technical bar and growing the next generation of researchers. What we need to see: PhD in Computer Science, Machine Learning, Statistics, or a related field, or equivalent experience. 15+ years of engineering and research experience in synthetic data generation, generative modeling, multimodal machine learning, or related areas.

Deep technical understanding of LLMs, how data shapes their pre-training, post-training, and RL stages, and inference frameworks such as vLLM or TGI. Proven track record of developing or maintaining software libraries used by a broad developer community. Experience building and optimizing scalable data pipelines for large-scale model training - throughput, distributed inference, and cost at cluster scale.

Strong publication record at premier venues such as NeurIPS, ICML, ICLR, ACL or similar. Ways to stand out from the crowd: Significant open-source contributions in ML or data tooling, with community adoption. Experience with multimodal generation or understanding (vision-language, document AI, video, or audio).

Experience generating data for agentic, tool-use, or reinforcement-learning post-training, including RL environment design. Background in differential privacy, de-identification, or synthetic data for regulated industries such as healthcare, finance, or government. Experience influencing model training decisions at frontier scale, or partnering directly with pre-training and post-training teams.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and talented people in the world working with us. If you are creative, autonomous, and passionate about building open-source tools that make AI safer and more private, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD. You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 8, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.


What Nvidia employees say

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Benefits

Hours and flexibility

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US