Conduct research on reinforcement learning (RL) related topics including large-scale closed-loop RL and VLA post-training with applications to robotics with emphasis on dexterous manipulation
Conduct research on reinforcement learning (RL) related topics including large-scale closed-loop RL and VLA post-training with applications to robotics with emphasis on dexterous manipulation
Conduct research on reinforcement learning (RL) related topics including large-scale closed-loop RL and VLA post-training with applications to robotics with emphasis on dexterous manipulation
Conduct research on reinforcement learning (RL) related topics including large-scale closed-loop RL and VLA post-training with applications to robotics with emphasis on dexterous manipulation
Conduct research on reinforcement learning (RL) related topics including large-scale closed-loop RL and VLA post-training with applications to robotics with emphasis on dexterous manipulation
Conduct research on reinforcement learning (RL) related topics including large-scale closed-loop RL and VLA post-training with applications to robotics with emphasis on dexterous manipulation
Conduct research on reinforcement learning (RL) related topics including large-scale closed-loop RL and VLA post-training with applications to robotics with emphasis on dexterous manipulation
Conduct research on reinforcement learning (RL) related topics including large-scale closed-loop RL and VLA post-training with applications to robotics with emphasis on dexterous manipulation
... edge reinforcement learning algorithms, conducting experiments, and optimizing these models to ... This will require close collaboration with our robotics, research, and engineering team. Your work ...
... edge reinforcement learning algorithms, conducting experiments, and optimizing these models to ... This will require close collaboration with our robotics, research, and engineering team. Your work ...
Strong background in robot dynamics , control, motion planning, reinforcement learning, imitation learning , or whole-body control. * Familiarity with modern robot learning methods such as PPO, SAC ...
Strong background in robot dynamics , control, motion planning, reinforcement learning, imitation learning , or whole-body control. * Familiarity with modern robot learning methods such as PPO, SAC ...
Robotics Autonomy ML Engineer - VLA & Manipulation
San Francisco, CA · On-site
$150K - $200K/yr
What you'll do * Design and develop a modular robot autonomy stack that composes ... Deep expertise in machine learning fundamentals, reinforcement learning, and associated frameworks ...
New
Robotics Autonomy ML Engineer - VLA & Manipulation
San Francisco, CA · On-site
$150K - $200K/yr
What you'll do * Design and develop a modular robot autonomy stack that composes ... Deep expertise in machine learning fundamentals, reinforcement learning, and associated frameworks ...
New
Dexmate is building the foundation for physical AI -- a unified platform that combines high-quality robotic hardware with a universal Physical AI OS. They are seeking Reinforcement Learning experts ...
Dexmate is building the foundation for physical AI -- a unified platform that combines high-quality robotic hardware with a universal Physical AI OS. They are seeking Reinforcement Learning experts ...
You will design, train, and deploy algorithms that enable robots to interact intelligently and ... Proficiency with advanced deep learning techniques and architectures as well as reinforcement ...
You will design, train, and deploy algorithms that enable robots to interact intelligently and ... Proficiency with advanced deep learning techniques and architectures as well as reinforcement ...
... robotics. Key work involves leveraging foundation models, reinforcement learning, simulation, and integrating ML models in production at scale. You will interface closely with operations teams to ...
... robotics. Key work involves leveraging foundation models, reinforcement learning, simulation, and integrating ML models in production at scale. You will interface closely with operations teams to ...
Senior Staff Machine Learning Engineer, Depot Automation
Mountain View, CA · Hybrid
$122K - $161K/yr
... robotics. Key work involves leveraging foundation models, reinforcement learning, simulation, and integrating ML models in production at scale. You will interface closely with operations teams to ...
Senior Staff Machine Learning Engineer, Depot Automation
Mountain View, CA · Hybrid
$122K - $161K/yr
... robotics. Key work involves leveraging foundation models, reinforcement learning, simulation, and integrating ML models in production at scale. You will interface closely with operations teams to ...
Senior Reinforcement Learning Engineer - Robotics
$122K - $168K/yr
Develop and refine end-to-end robot motion controllers using reinforcement learning, imitation learning, or other advanced techniques. * Design, execute, and analyze experiments to evaluate RL ...
Senior Reinforcement Learning Engineer - Robotics
$122K - $168K/yr
Develop and refine end-to-end robot motion controllers using reinforcement learning, imitation learning, or other advanced techniques. * Design, execute, and analyze experiments to evaluate RL ...
Senior Reinforcement Learning Engineer - Robotics
Santa Clara, CA · On-site
$122K - $168K/yr
Develop and refine end-to-end robot motion controllers using reinforcement learning, imitation learning, or other advanced techniques. * Design, execute, and analyze experiments to evaluate RL ...
Senior Reinforcement Learning Engineer - Robotics
Santa Clara, CA · On-site
$122K - $168K/yr
Develop and refine end-to-end robot motion controllers using reinforcement learning, imitation learning, or other advanced techniques. * Design, execute, and analyze experiments to evaluate RL ...
Senior Staff Research Engineer - Reinforcement Learning for AI Agents
Santa Clara, CA · On-site
$122K - $168K/yr
Required : • MS or PhD in Computer Science, AI, Machine Learning, Robotics, or a related field. • Strong background in reinforcement learning or machine learning. • Experience implementing RL ...
Senior Staff Research Engineer - Reinforcement Learning for AI Agents
Santa Clara, CA · On-site
$122K - $168K/yr
Required : • MS or PhD in Computer Science, AI, Machine Learning, Robotics, or a related field. • Strong background in reinforcement learning or machine learning. • Experience implementing RL ...
Senior Staff Research Engineer - Reinforcement Learning for AI Agents
Santa Clara, CA · On-site
$122K - $168K/yr
Required : • MS or PhD in Computer Science, AI, Machine Learning, Robotics, or a related field. • Strong background in reinforcement learning or machine learning. • Experience implementing RL ...
Senior Staff Research Engineer - Reinforcement Learning for AI Agents
Santa Clara, CA · On-site
$122K - $168K/yr
Required : • MS or PhD in Computer Science, AI, Machine Learning, Robotics, or a related field. • Strong background in reinforcement learning or machine learning. • Experience implementing RL ...
Strong background in robot dynamics , control, motion planning, reinforcement learning, imitation learning , or whole-body control. * Familiarity with modern robot learning methods such as PPO, SAC ...
Strong background in robot dynamics , control, motion planning, reinforcement learning, imitation learning , or whole-body control. * Familiarity with modern robot learning methods such as PPO, SAC ...
Senior Staff Research Engineer - Reinforcement Learning for AI Agents
Santa Clara, CA · On-site
$122K - $168K/yr
Required : • MS or PhD in Computer Science, AI, Machine Learning, Robotics, or a related field. • Strong background in reinforcement learning or machine learning. • Experience implementing RL ...
Senior Staff Research Engineer - Reinforcement Learning for AI Agents
Santa Clara, CA · On-site
$122K - $168K/yr
Required : • MS or PhD in Computer Science, AI, Machine Learning, Robotics, or a related field. • Strong background in reinforcement learning or machine learning. • Experience implementing RL ...
Figure is an AI robotics company developing autonomous general-purpose humanoid robots. They are seeking a Helix AI Engineer, Reinforcement Learning to develop learning systems that enable robots to ...
Figure is an AI robotics company developing autonomous general-purpose humanoid robots. They are seeking a Helix AI Engineer, Reinforcement Learning to develop learning systems that enable robots to ...
Reporting to the Head of AI / Reinforcement Learning Engineering, you will design, train, and ... MS or PhD in Computer Science, Robotics, Operations Research, or a related field with a focus on ...
Reporting to the Head of AI / Reinforcement Learning Engineering, you will design, train, and ... MS or PhD in Computer Science, Robotics, Operations Research, or a related field with a focus on ...
Figure is an AI robotics company developing autonomous general-purpose humanoid robots. They are seeking a Helix AI Engineer, Reinforcement Learning to develop learning systems that enable robots to ...
Figure is an AI robotics company developing autonomous general-purpose humanoid robots. They are seeking a Helix AI Engineer, Reinforcement Learning to develop learning systems that enable robots to ...
Reinforcement Learning Robotics information
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 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 is the difference between Reinforcement Learning Robotics vs Machine Learning Engineer?
| Aspect | Reinforcement Learning Robotics | Machine Learning Engineer |
|---|---|---|
| Required Credentials | Degree in Robotics, Computer Science, or related fields; knowledge of reinforcement learning | Degree in Computer Science, Data Science, or related fields; expertise in machine learning algorithms |
| Work Environment | Robotics labs, manufacturing, autonomous systems | Tech companies, data-driven projects, software development |
| Industry Usage | Autonomous robots, industrial automation, research | Data 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.
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Posted 20 days ago
Job description
About Applied Intuition
Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company's solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co.
We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments.
About the role:
We are looking for multiple passionate Research Interns to join the Research Group at Applied Intuition. The mission of the group is to create cutting-edge technology enabling next-generation physical AI, with emphasis on the two most challenging applications reshaping our everyday life: end-to-end autonomous driving and robotic generalist. We have a group composed of leading experts from top institutions and companies, recognized for their exceptional academic and industry contributions-including eight Best Paper awards at premier conferences and journals such as CVPR and ICRA. Learn more at appliedintuition.com/research.
Supported by industry-leading tools and infra, researchers can access millions of miles of data from large fleets, and deploy methods they develop into various autonomous and robotic systems including self-driving cars/trucks, autonomous mining/construction machines, humanoid robots and dexterous hands. In addition to your research contributions, you will contribute to and learn from best practices in the autonomy and robotics industries within our fast-paced and customer-focused culture. Improvements deployed to our system immediately help our customers with their programs and deliver value to our business.
At Applied Intuition, you will:
- Conduct research on reinforcement learning (RL) related topics including large-scale closed-loop RL and VLA post-training with applications to robotics with emphasis on dexterous manipulation
- Diving into fundamental and relevant topics on RL with broader applications
- Work closely with the Research Scientists and Engineers on high quality research publications for submission to top-tier conferences
We're looking for someone who has:
- Strong research background and skills on relevant topics, and the ability to work both independently and collaboratively on projects
- Current PhD (or MSc) studies in machine learning, computer vision and graphics, robotics
- Passion for next-generation, scalable autonomy and robotics
Don't meet every single requirement? If you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.
Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws.