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Reinforcement Learning Engineer Jobs in Seattle, WA

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

ML Engineer (Senior)

Seattle, WA · On-site

$140K - $220K/yr

NLP, Computer Vision, Time-Series, or Reinforcement Learning * Generative AI and LLM-related capabilities (e.g., prompt engineering, RAG, fine-tuning, LangChain, model evaluation tooling) * MLOps and ...

Showing results 41-60

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 23, 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 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 are popular job titles related to Reinforcement Learning Engineer jobs in Seattle, WA?

For Reinforcement Learning Engineer jobs in Seattle, WA, the most frequently searched job titles 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 91% Full Time, and 9% Contract. Highlights an 90% In-person, and 10% Remote job distribution, with an average salary of $131,931 per year, or $63.4 per hour.

AIML - Machine Learning Research

Apple

Seattle, WA

$142K - $263K/yr

Full-time

Medical, Dental, Retirement

Re-posted 7 days ago


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us strengthening each other’s ideas. That happens because every one of us believes that we can make something wonderful and share it with the world, changing lives for the better!
In this organization, we work hard to bring the best user experiences powered by Apple Intelligence. Our team is instrumental in powering and enhancing features across a range of Apple products, including Siri, Spotlight, Safari, Messages, and more. We are an Applied ML team pushing the limits of question answering, assistant response ranking, summarization, and search technologies, while also responsible for a production service.
As part of this group, you will be doing large scale machine learning and deep learning research and development to improve Open Domain Question Answering (using both structured knowledge graph data and unstructured web data) and Summarization as well as developing fundamental building blocks needed for Artificial Intelligence. This involves developing sophisticated machine learning and large language models (LLMs) to understand user queries, retrieve and rank relevant documents across multiple sources and synthesize information across documents to provide user with a direct answer that best satisfies their intent and information seeking needs. Additionally, you will research and develop the state-of-the-art LLMs for summarizing personal data such as emails, messages, and notifications.
You will also work with researchers and data scientists to develop, fine-tune, and evaluate domain specific Large Language Models for various tasks and applications in Apple’s AI powered products and conduct applied research to transfer the cutting edge research in generative AI to production ready technologies.
Description
In this role, you will work on LLM based question answering and Apple Intelligence features to provide concise, accurate, and grounded information to users to help them complete their tasks quickly on Apple devices.
Your core responsibilities will include:
* Designing and developing advanced Reinforcement Learning technologies in the post-training of generative model, and delivering the end-user experience.
* Driving cross-functional technical initiatives, collaborating with research, engineering and production teams to translate theoretical advances into deployable systems.
* Developing novel and cutting-edge RL algorithms and improving existing ones.
* Staying up to date with the latest RL research and integrate best practices into the team's workflow.
* Working on the end-to-end ML lifecycle: algorithm design and implementation, data collection, model training, evaluation, and deployment.
Preferred Qualifications
Deep expertise in reinforcement learning-based post-training on LLM models, reward modeling, RLHF, RLAIF, Chain-of-thought, and agentic AI R&D.
Experienced researcher with publications in areas of machine learning, including natural language processing
Deep understanding of cutting edge RL algorithms and large language model.
Deep understanding in LLM pre-training, post-training.
Strong product intuition and ownership
Excellent communication skills
Minimum Qualifications
1+ years of ML experiences in search, natural language processing/understanding. Conversational AI.
Proven experience for LLM post training, including but not limited to SFT, RLHF, RLAIF, Reward Modeling, Chain-of-thought, agentic LLM.
Hands-on experience building RL pipelines and training agents in simulation or real-world environments.
Experienced researcher in areas of machine learning, including natural language or speech
Growth mindset and ability to learn new technologies
MS or Ph.D. in Computer Science, Machine Learning with a specialty in reinforcement learning, or a related field
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $142,300 and $263,300, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976