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Reinforcement Learning Robotics Jobs in Edison, NJ

New York University

RESEARCH SCHOLAR

New York, NY · On-site

$27/hr

Hao Su ( at NYU Tandon School of Engineering is seeking to hire a Part Time Research Scholar (Non-PhD) to work on mechatronics design, control, and reinforcement learning for wearable robots ...

Rogo

AI Researcher

Manhattan, NY · On-site

... with deep reinforcement learning in any context (autonomous vehicles, robotics, or LLMs) • Experience working with data generated by human experts for model training • Financial services ...

New York University

Research Associate

New York, NY · On-site

$48K - $65K/yr

Hao Su ( at NYU Tandon School of Engineering is seeking to hire a Full time Research Associate to work on mechatronics design, control, and reinforcement learning for wearable robots, surgical robots ...

Amazon

Senior Applied Scientist, Fauna

New York, NY · On-site

$100K - $136K/yr

... between robots and their environments. Key job responsibilities - Develop controllers that leverage reinforcement learning, imitation learning, or other advanced AI techniques to achieve natural ...

Amazon

ML Infrastructure Engineer, Fauna

New York, NY · On-site

$117K - $154K/yr

You'll bring deep expertise in reinforcement learning, computer vision, and supervised learning applied to robotics and embodied systems. You also need to think seriously about training ...

Amazon

ML Infrastructure Engineer, Fauna

New York, NY

$117K - $154K/yr

You'll bring deep expertise in reinforcement learning, computer vision, and supervised learning applied to robotics and embodied systems. You also need to think seriously about training ...

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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?

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 Edison, NJ? For Reinforcement Learning Robotics jobs in Edison, NJ, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Robotics jobs in Edison, NJ look for? The top searched job categories for Reinforcement Learning Robotics jobs in Edison, NJ are:
What cities near Edison, NJ are hiring for Reinforcement Learning Robotics jobs? Cities near Edison, NJ with the most Reinforcement Learning Robotics job openings:
Reinforcement Learning Robotics jobs near you
AI Research Scientist, Reinforcement Learning

AI Research Scientist, Reinforcement Learning

Meta

New York, NY • On-site

$122K - $181K/yr

Full-time

Re-posted 20 days ago

Meta rating

7.5

Company rating: 7.5 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

135th of 209 rated software companies

Job description

Meta's Fundamental AI Research lab is seeking a Research Scientist to drive foundational research aimed at advancing physical AI capabilities. We seek to generate advanced engineer designs such as robotic hardware, mobile vehicles, and novel semiconductors. This role will involve heavy software research engineering, such large-scale data manipulation and simulator integration.
Responsibilities
Explore and develop novel post-training paradigms for LLMs using reinforcement learning
• Explore and develop novel LLM post-training recipes using 3D data
• Integrate large-scale simulation into LLM post-training
• Explore mechanical, aerospace, civil, and other engineering disciplines and how to enable LLMs to solve key problems in these domains
Minimum Qualifications
• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
• Currently has or is in the process of obtaining a PhD degree in Artificial Intelligence, Computer Vision (3D), Physical AI, Machine Learning, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
• Research experience in at least one of the following research areas: reinforcement learning, representation learning, self-supervised learning, multimodal learning, robotics policy development, computer vision (3D), egocentric perception, embodied AI and/or LLMs, control theory, optimization algorithms
• Experience in C/C++ and Python and deep learning frameworks (e.g., PyTorch, TensorFlow)
• Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment
Preferred Qualifications
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, AAAI, JMLR and Computer Vision (CVPR, ICCV, ECCV, TPAMI)
• This position will require knowledge of post-training for LLMs using reinforcement learning techniques. It will also involve novel modalities such as 3D and engineering domain-specific simulators, so computer vision expertise in 3D is welcome as well
• Experience integrating and debugging prototype/scientific software-hardware systems including mechanical, aerospace, or civil engineering domain-specific simulation
• Experience working and communicating cross-functionally in a team environment
• Prior work experience in the fields of mechanical, aerospace, civil engineering or other engineering domains
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.
Equal Employment Opportunity
Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here.

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