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Reinforcement Learning Engineer Jobs in Seattle, WA

Mentor ML engineers and raise the organization's ML bar Qualifications * PhD or equivalent ... Experience with optimization techniques, including reinforcement learning (RL), Bayesian methods ...

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 ...

Backend Engineer - Remote

Seattle, WA Β· Remote

$80 - $120/hr

Create reinforcement learning environments for software engineering tasks. * Design tasks involving bug fixing, feature development, refactoring, and performance optimization . * Build deterministic ...

Backend Engineer - Remote

Seattle, WA Β· Remote

$80 - $120/hr

Create reinforcement learning environments for software engineering tasks. * Design tasks involving bug fixing, feature development, refactoring, and performance optimization . * Build deterministic ...

Applied AI Engineer

Seattle, WA Β· On-site

$130K - $220K/yr

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 ...

Showing results 21-40

Reinforcement Learning Engineer information

See Seattle, WA salary details

$43.2K

$131.9K

$217.9K

How much do reinforcement learning engineer jobs pay per year?

As of Sep 15, 2026, the average yearly pay for reinforcement learning engineer in Seattle, WA is $131,857.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,500.00 and $172,400.00 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 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, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $131,931 per year, or $63.4 per hour.

Staff/Senior Machine Learning Engineer, Search & Knowledge Platform

Seattle, WA β€’ On-site

Socket.dev
Network SecurityΒ β€’Β 1 - 10 employees

$139K - $183K/yr

Other

Posted 28 days ago


Job description

Apple is where individual imaginations come 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! Here, you’ll do more than join something β€” you’ll add something. The Information Intelligence team is redefining how billions of people use their devices to get information. We are an Applied ML team pushing the limits of question answering, assistant response ranking, and search technologies, while also responsible for a production service. We are part of a wider effort to power information across a variety of Apple products – including Siri, Spotlight, Safari, Messages, Lookup, and more. As a Staff/Senior Machine Learning Engineer, you play a critical role in developing world-class Search and Q&A experiences for Apple customers with cutting-edge search technologies and large language models.

DESCRIPTION

As a member of our fast-paced group, you’ll have the unique and rewarding opportunity to shape upcoming products from Apple. Our team includes a diversity of backgrounds from applied scientists with a focus in NLP to experienced distributed systems engineers. As such, we are looking for candidates with in-depth understanding of machine learning fundamentals, applied machine learning experience, and strong software engineering skills. Our team is responsible for delivering next-generation Search and Question Answering systems across Apple products including Siri, Safari, Spotlight, and more. This is your chance to shape how people get information by leveraging your Search and applied machine learning expertise along with robust software engineering skills. You will collaborate with outstanding Search and AI engineers on large scale machine learning to improve Query Understanding, Retrieval, and Ranking, developing fundamental building blocks needed for AI powered experiences such as fine-tuning and reinforcement learning. This involves pushing the boundaries on document retrieval and ranking, developing sophisticated machine learning models, using embeddings and deep learning to understand the quality of matches. It also includes online learning to react quickly to change and natural language processing to understand queries. You will work with petabytes of data and combine information from multiple structured and unstructured sources to provide the best results and accurate answers to satisfy users' information-seeking needs. As part of our team, you will be leveraging and improving upon the latest deep learning techniques, such as LLM and RAG, in order to understand queries and user intents, rank documents, and find useful answers to users’ questions. Our team is responsible for training, fine-tuning and deploying these models at scale, using the latest advances for online inference optimization.

Following is the primary list of responsibilities for an ML engineer in the team:

MINIMUM QUALIFICATIONS

MS in Computer Science or related field 10+ years of work experience in machine learning, deep learning or related field 10+ years experience in shipping Search and Q&A technologies and ML systems Excellent programming skills in mainstream programming languages such as C++, Python, Scala, and Go Experience delivering tool

PREFERRED QUALIFICATIONS

PhD in Computer Science, Artificial Intelligence, Machine Learning, Information Retrieval, Data Science or related field Strong industry background and experience in search and related technologies (LLMs, Machine Learning, NLP, Information Retrieval, Question Answering) Strong and validated experience of ML development and production systems Experience working with foundation models and LLMs

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