ZipRecruiter

Log In

1

Reinforcement Learning Robotics Jobs in Seattle, WA

Meta

VP Robotics

Redmond, WA

$486K/yr

Working familiarity with modern robot learning and how it translates into product capability: reinforcement learning, imitation learning, sim-to-real transfer, and manipulation * Experience retaining ...

Nvidia

Senior Robotics Research Scientist

Seattle, WA

$112K - $142K/yr

The Seattle Robotics Lab is focused on fundamental and applied robotics research across the full robotics stack, including perception, planning, control, reinforcement learning, imitation learning ...

CoreWeave

Senior Applied ML Engineer

Bellevue, WA · On-site

$117K - $162K/yr

Bachelor's, Master's, or PhD degree in Computer Science, Machine Learning, Robotics, or a related ... reinforcement learning, and on-policy distillation * Experience developing, evaluating, and ...

CoreWeave

Senior Applied ML Engineer

Seattle, WA · On-site

$118K - $163K/yr

Bachelor's, Master's, or PhD degree in Computer Science, Machine Learning, Robotics, or a related ... reinforcement learning, and on-policy distillation * Experience developing, evaluating, and ...

CoreWeave

Senior Applied ML Engineer

Bellevue, WA · On-site

$117K - $162K/yr

Bachelor's, Master's, or PhD degree in Computer Science, Machine Learning, Robotics, or a related ... reinforcement learning, and on-policy distillation * Experience developing, evaluating, and ...

previous page

Showing results 41-60

All JobsReinforcement Learning Robotics JobsReinforcement Learning Robotics Jobs in Seattle, WA

Reinforcement Learning Robotics information

What is reinforcement learning in robotics?

Reinforcement learning in robotics refers to a type of machine learning where robots learn to perform tasks through trial and error, receiving feedback from their actions in the form of rewards or penalties. This approach allows robots to autonomously develop complex behaviors by interacting with their environment, rather than relying solely on pre-programmed instructions. Reinforcement learning is especially useful for tasks that are difficult to model explicitly, such as walking, grasping, or navigation. Over time, the robot improves its performance by maximizing the cumulative reward, leading to more efficient and adaptive behaviors.

What are some common challenges faced when implementing reinforcement learning algorithms in robotics projects?

One common challenge in this role is bridging the gap between simulation and real-world environments, as algorithms that perform well in simulation may not translate directly to physical robots due to unpredictable variables and hardware limitations. Additionally, ensuring the safety and stability of the robot during training is crucial, since trial-and-error learning can sometimes result in unintended behaviors or hardware damage. Collaboration with hardware engineers and domain experts is often necessary to fine-tune models, interpret results, and iterate on solutions. Overcoming these challenges requires patience, adaptability, and strong communication skills within a multidisciplinary team.

What are the key skills and qualifications needed to thrive as a reinforcement learning robotics engineer, and why are they important?

To thrive as a Reinforcement Learning Robotics Engineer, you need a strong background in robotics, machine learning, and programming, typically supported by a degree in computer science, engineering, or a related field. Expertise with frameworks like TensorFlow or PyTorch, experience with simulation environments (such as Gazebo or ROS), and familiarity with reinforcement learning algorithms are essential. Strong problem-solving skills, creativity, and effective communication set standout professionals apart in this rapidly evolving field. These skills enable engineers to develop intelligent robotic systems that adapt and learn efficiently, driving innovation and practical deployment in real-world environments.

What is the difference between Reinforcement Learning Robotics vs Machine Learning Engineer?

AspectReinforcement Learning RoboticsMachine Learning Engineer
Required CredentialsDegree in Robotics, Computer Science, or related fields; knowledge of reinforcement learningDegree in Computer Science, Data Science, or related fields; expertise in machine learning algorithms
Work EnvironmentRobotics labs, manufacturing, autonomous systemsTech companies, data-driven projects, software development
Industry UsageAutonomous robots, industrial automation, researchData analysis, predictive modeling, AI applications

Reinforcement Learning Robotics focuses on applying reinforcement learning techniques to control and optimize robotic systems, often in physical environments. Machine Learning Engineers develop algorithms for a broad range of applications, including data analysis and predictive modeling. While both roles require knowledge of machine learning, Reinforcement Learning Robotics emphasizes robotics and real-world interaction, whereas Machine Learning Engineers work across various industries with software-based solutions.

What are popular job titles related to Reinforcement Learning Robotics jobs in Seattle, WA?

For Reinforcement Learning Robotics jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Reinforcement Learning Robotics jobs in Seattle, WA look for?

The top searched job categories for Reinforcement Learning Robotics jobs in Seattle, WA are:

Reinforcement Learning Robotics jobs near you

VP Robotics

Redmond, WA

Meta
Internet and IT • 10K+ employees
Learn more about Metaexternal

$486K/yr

Full-time

Posted 8 days ago

Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

Job description

You will lead Meta Robotics Studio and own the delivery of Meta's robotics products — from architecture and industrial design through development, manufacturing, and launch. You will be accountable for the roadmap, the milestones, and the shipped result: robots/ humanoids in the hands of real people, at quality, at cost, and on schedule. You will lead an organization spanning hardware engineering, embodied AI and machine learning, systems software, manufacturing, and operations, and you will build the execution muscle that turns deep technical capability into products people use every day.
VP Robotics Responsibilities:
  • Own the robotics product roadmap and delivery plan — the milestones, the schedule, and the shipped outcome — and hold the organization accountable to it.
  • Drive products end to end through the full development lifecycle: architecture, industrial design, prototyping, design validation, production validation, ramp, and launch.
  • Own hardware productization at scale — manufacturability, quality, reliability, yield, and cost of goods — in partnership with Supply Chain and Manufacturing.
  • Make and defend the consequential product decisions: form factor, platform architecture, build-versus-buy, and what ships in which release.
  • Establish the operating cadence, program management discipline, and execution bar required to ship complex hardware and software on a predictable schedule.
  • Direct applied technical investment toward shipping outcomes — ensuring embodied AI, machine learning, and systems work is sequenced against product milestones.
  • Build, manage and support diverse teams of engineering directors and managers across multiple sites.
  • Provide both technical and organizational leadership.
  • Form cross-functional and cross-discipline partnerships across MSL, TBD, Reality Labs Research, Product, Design, Safety, Supply Chain, Manufacturing, Legal, and Policy.,.
  • Establish effective strategies and execute against them.
  • Own the product-quality, safety, and reliability standard for physical robotic systems, including regulatory and certification requirements for consumer deployment.
  • Foster an environment of respect, integrity, inclusion, and innovation.
  • Recruit and retain top talent across hardware, software, AI, and manufacturing disciplines.

Minimum Qualifications:
  • 15+ years of technical industry experience
  • 10+ years of management experience
  • Experience as VP or C-level of an engineering organization at a company operating at scale
  • Experience managing and scaling organizations
  • Experience shipping physical hardware products to customers at volume, with ownership of the outcome
  • Experience owning a multi-year hardware and software program through to launch, including schedule, quality, and cost commitments
  • Experience leading hardware productization in partnership with supply chain, manufacturing, and contract manufacturers
  • Experience integrating advanced software or AI capabilities into shipping consumer or commercial products
  • Experience initiating and driving projects to completion with minimal guidance
  • Experience analyzing, interpreting, and leveraging data to make business decisions

Preferred Qualifications:
  • Experience managing robotics and engineering products at scale
  • Experience bringing a new hardware product category from concept to high-volume production
  • Experience with new product introduction, design and production validation, manufacturing ramp, and supplier qualification
  • Experience owning cost of goods, bill of materials, and margin structure for a hardware product line
  • Experience with consumer product safety, regulatory certification, and reliability qualification for physical autonomous systems
  • Working familiarity with modern robot learning and how it translates into product capability: reinforcement learning, imitation learning, sim-to-real transfer, and manipulation
  • Experience retaining senior engineering and AI talent through organizational or leadership change
  • Advanced degree in Robotics, Engineering, Computer Science, Machine Learning, or a related field

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$486,000/year to $527,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

What Meta employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply