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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 ...

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 ...

In this hands-on engineering role, you'll develop machine learning pipelines, integrate robotic ... Experience with reinforcement learning, diffusion models, vision-language-action models, or robotic ...

In this hands-on engineering role, you'll develop machine learning pipelines, integrate robotic ... Experience with reinforcement learning, diffusion models, vision-language-action models, or robotic ...

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 Aug 5, 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 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 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 July 2026, with employment types broken down into 71% Full Time, and 29% Contract. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $131,857 per year, or $63.4 per hour.

Machine Learning Engineer, Information Security

Apple

Seattle, WA

$142K - $263K/yr

Full-time

Medical, Dental, Retirement

Re-posted 15 hours ago


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 676 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

Join Apple’s Information Security Machine Learning (ISML) team, where we are redefining cybersecurity through data-driven intelligence. Our mission is to transform traditional reactive security measures into autonomous systems that proactively detect and defend against threats. We achieve this through cutting-edge research, applied science, and robust infrastructure development. We are seeking a highly motivated and talented Machine Learning Engineer to join our dynamic and growing team. You will play a pivotal role in designing, developing, and deploying machine learning models that power our advanced security products and services. This is an incredible opportunity to make a real world impact by building intelligent systems that detect and prevent advanced threats, enhance critical security processes, and protect Apple and our customers.
Description
The Security ML Engineer will bring their expertise in machine learning to the problems and opportunities facing Information Security at Apple. You will contribute to the Autonomous Security program by developing production ready AI/ML systems using Apple’s internal platforms, cloud services, and local compute environments.
You will translate research to design, building and deploying machine learning models for security use cases, leveraging generative AI, statistical modeling, reinforcement learning, and data science to address complex security challenges. You will collaborate with cross-functional teams including security teams, software engineers, and researchers to prototype and scale AI/ML driven security solutions. You will own end-to-end ML workflows: data exploration, model development, evaluation metrics design, deployment, and monitoring.
Preferred Qualifications
Ph.D. in a technical field such as Computer Science, Engineering, Statistics, or related disciplines.
In-depth knowledge of ML algorithms, including supervised/unsupervised learning, deep learning (CNNs, RNNs, LSTMs), and large language models.
Industry experience in deploying ML and generative AI solutions in cybersecurity contexts.
Familiarity with cloud platforms (e.g., AWS, GCP) and their security offerings is a plus.
Experience with large scale data processing and analysis using tools such as Apache Spark.
Experience working in a key security process, such as Incident Response, Threat Intelligence, or Vulnerability Management.
Experience with specific security tools and technologies (e.g., SIEM, IDS/IPS, endpoint security solutions).
Contributions to open-source security or machine learning projects.
Publications or talks at top-tier ML or security conferences.
Additional proficiency in C++ or Swift is a plus
Minimum Qualifications
BSc or Masters degree in Machine Learning, Data Science, Computer Science, Information Security, Mathematics, Statistics, or related field.
Strong programming skills in Python and Scala; experience with ML libraries such as TensorFlow, PyTorch, HuggingFace, and Scikit-learn.
Hands-on experience with full ML model lifecycle: from experimentation to deployment and monitoring.
Solid grasp of security fundamentals including network security, incident response, threat modeling, and vulnerability management.
Excellent written and verbal communication skills, with the ability to present technical concepts clearly to varied audiences.
Familiarity with CI/CD workflows and ML pipelines .
Experience operating, and scaling production services in cloud native environments.
Experience deploying models on CUDA devices using tools like TensorFlow or Torch.
Proven experience building generative AI applications for real-world use cases.
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