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Reinforcement Learning Engineer Jobs in Seattle, WA

In this role, you'll work closely with a small, dynamic team of AI researchers and engineers exploring reinforcement learning, transformer-based architectures, and diffusion models. You'll be ...

The Role We're looking for an Applied AI Engineer to help build the next generation of agentic ... Background in reinforcement learning or data-centric AI approaches. Compensation The salary range ...

Senior Software Engineer, AI Networking

Seattle, WA · On-site

$139K - $183K/yr

Hands-on experience developing and deploying various learning algorithms (e.g., reinforcement ... Strong programming capabilities in Python, Bash, and C++. * A collaborative teammate with effective ...

Designing and developing advanced Reinforcement Learning technologies in the post-training of ... Driving cross-functional technical initiatives, collaborating with research, engineering and ...

Showing results 21-40

Reinforcement Learning Engineer information

See Seattle, WA salary details

$43.3K

$131.9K

$218.1K

How much do reinforcement learning engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for reinforcement learning engineer in Seattle, WA is $131,931.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,500.00 and $172,500.00 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 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 job categories do people searching Reinforcement Learning Engineer jobs in Seattle, WA look for? The top searched job categories for Reinforcement Learning Engineer jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Reinforcement Learning Engineer jobs? Cities near Seattle, WA with the most Reinforcement Learning Engineer job openings:
Infographic showing various Reinforcement Learning Engineer job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $131,931 per year, or $63.4 per hour.

Machine Learning Engineer, Next-Generation Recommendation Systems

Unitytech

Bellevue, WA • On-site, Remote

$127K - $191K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 6 days ago


Job description

The opportunity
Unity's Vector AI team builds the machine learning systems that decide which ads reach which players - across billions of monthly users on the world's leading game engine. Recommendation and ranking systems are the core of this work: predicting user value, optimizing bids, and delivering outcomes for advertisers at massive scale.

We are building the next generation of these systems. The frontier has shifted - large language models, reinforcement learning from human feedback, and agentic AI are reshaping what recommendation systems can do. We are looking for PhD graduates who have worked at that frontier and want to bring those ideas into production systems that matter.

What you'll be doing

  • Design, build, and evaluate next-generation ranking and recommendation models that incorporate LLMs, RLHF, and preference learning to improve ad relevance and user experience.
  • Develop user understanding systems - conversion prediction, behavioral modeling, and value estimation - that operate across billions of impressions.
  • Apply reinforcement learning and optimization techniques to bidding strategy, auction dynamics, and real-time ad delivery.
  • Design and run rigorous experiments using causal inference, A/B testing, and offline evaluation frameworks to measure and improve model quality.
  • Partner with engineering to bring research ideas into production, working across the full pipeline from training data to deployed model.
  • Communicate findings clearly to technical and non-technical stakeholders across engineering, product, and business teams.

What we're looking for

  • PhD in Computer Science, Machine Learning, Statistics, or a related field (graduating 2026 or recent graduate).
  • Strong research foundations in one or more of: recommendation systems, reinforcement learning, LLM post-training or alignment, human-AI collaboration, probabilistic modeling, or optimization.
  • Experience working with large-scale data and ML systems, whether through research or industry internships.
  • Fluency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
  • A track record of rigorous, high-quality research - publications at top venues (NeurIPS, ICML, ICLR, KDD, RecSys, ACL, WWW, or similar) are a strong signal.
  • Strong written and verbal communication skills - able to make complex ideas accessible across technical and non-technical audiences.

You might also have

  • Industry experience in ads, recommendation, or user understanding systems (internship experience counts).
  • Hands-on experience with production ML pipelines - training at scale, feature engineering, or experimentation infrastructure.
  • Experience applying LLMs or generative models to ranking, retrieval, or structured prediction problems.
  • Familiarity with agentic AI approaches - multi-step reasoning, tool use, or human-AI collaboration frameworks.
  • Exposure to causal inference, uplift modeling, or A/B testing at scale.
  • Genuine curiosity about applied research and the drive to see ideas through to impact.

Additional information

  • Relocation support is not available for this position
$127,400.00 - $191,200.00

This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate's relevant experience, professional background, and skill set.

Benefits


At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.


Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.


While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program

Life at Unity


Unity [NYSE: U] is the world's leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D - closing the gap between ideas and reality. For more information, please visit www.unity.com.


Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.


This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.
This posting is intended to fill an existing vacancy, and we are committed to providing applicants with updates throughout the hiring process in accordance with applicable law.


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