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Robotic Manipulation Engineer Jobs (NOW HIRING)

Diligent Robotics

ML Engineer, Manipulation

We envision a future powered by robots that work seamlessly with human teams. We build artificial ... As an ML Engineer, Manipulation, you will develop and deploy learning-based manipulation systems ...

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How much do robotic manipulation engineer jobs pay per year?

As of Jun 7, 2026, the average yearly pay for robotic manipulation engineer in the United States is $105,605.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,500.00 and $127,000.00 per year, depending on experience, location, and employer.

What are some typical interdisciplinary collaborations for a Robotic Manipulation Engineer, and how do these partnerships impact daily work?

Robotic Manipulation Engineers frequently collaborate with mechanical engineers, computer vision specialists, and software developers to design, test, and refine robotic systems. These collaborations ensure that manipulation algorithms are compatible with hardware constraints and can interpret sensory data accurately. Working closely with cross-functional teams not only accelerates problem-solving but also exposes engineers to a variety of perspectives, enhancing both technical and communication skills. Daily responsibilities often include joint troubleshooting sessions, integration meetings, and coordinated field tests to validate system performance.

What is the difference between Robotic Manipulation Engineer vs Robotic Software Engineer?

AspectRobotic Manipulation EngineerRobotic Software Engineer
CredentialsBachelor's or Master's in Robotics, Mechanical, or Electrical EngineeringBachelor's or Master's in Computer Science, Software Engineering, or Robotics
Work EnvironmentResearch labs, manufacturing, automation companiesSoftware development firms, robotics companies, tech startups
Industry UsageFocus on physical robot control and manipulation tasksFocus on software development, algorithms, and system integration

Robotic Manipulation Engineers specialize in designing and implementing robotic systems that physically manipulate objects, often working closely with hardware. Robotic Software Engineers develop the software that powers robotic systems, focusing on algorithms, control systems, and system integration. While both roles require a background in robotics and programming, their primary focus differs: one on physical manipulation and hardware, the other on software development and system architecture.

What are the key skills and qualifications needed to thrive as a Robotic Manipulation Engineer, and why are they important?

To thrive as a Robotic Manipulation Engineer, you need a strong background in robotics, mechanical engineering, and computer science, often supported by an advanced degree and experience in robotic systems. Familiarity with ROS (Robot Operating System), simulation tools like Gazebo, and programming languages such as Python or C++ is typically required. Problem-solving ability, creativity, and strong teamwork skills make someone stand out in this position. These skills are crucial for designing, implementing, and optimizing robotic systems that reliably interact with complex, real-world environments.

What is a Robotic Manipulation Engineer?

A Robotic Manipulation Engineer is a professional who designs, develops, and tests robotic systems capable of interacting with and manipulating objects in their environment. Their work involves creating algorithms and hardware that enable robots to perform tasks such as picking, placing, assembling, or sorting items with precision and reliability. They often use principles from mechanical engineering, computer vision, artificial intelligence, and control systems to solve complex manipulation challenges. These engineers are critical in industries like manufacturing, logistics, healthcare, and research. Their expertise helps automate processes that are difficult, repetitive, or dangerous for humans.

Research Scientist, Dexterous Manipulation & Robot Learning

Lila Sciences

Cambridge, MA

Other

Posted 16 days ago

Job description

Your Impact at LILA

As a Robotics Scientist at Lila, you will lead the research and development of autonomous robotic systems that serve as the intelligent physical infrastructure of our scientific superintelligence platform. You'll develop novel algorithms and deploy intelligent robotic solutions that interact seamlessly with human scientists and complex lab environments. Your work will accelerate our mission by enabling fully autonomous workflows for scientific discovery, combining cutting-edge robotics, machine learning, and systems engineering.

What You'll Be Building

  • Pioneering approaches for precise and dexterous robotic manipulation that leverage foundation models, reinforcement learning, diffusion-based methods, and human guidance to enable adaptive and intelligent robotic systems capable of complex tasks across diverse scientific environments
  • Developing novel human-robot interaction frameworks that incorporate imitation learning, and learning from human guidance, feedback, demonstrations and corrections, creating intelligent robotic agents that can seamlessly integrate with human scientific workflows and rapidly adapt to new experimental contexts
  • Advancing dexterous manipulation research through cutting-edge machine learning approaches, including diffusion models and adaptive learning algorithms, that synthesize multi-modal sensing (tactile, visual, and language) to develop generative skill representation sand sophisticated motor learning policies for intelligent robotic systems
  • Designing autonomous robotic systems with trust calibration mechanisms, enabling intelligent agents that can dynamically adjust their behaviors based on contextual information in complex scientific tasks

What You'll Need to Succeed

  • Ph.D. in Robotics, Machine Learning, Computer Science, or a related field with demonstrated expertise in foundation models for robotic learning
  • Advanced proficiency in reinforcement learning, diffusion-based methods, imitation learning, and adaptive learning algorithms for robotic manipulation
  • Expert-level experience with machine learning frameworks (PyTorch, TensorFlow) and deep learning architectures for developing foundation models, with specific expertise in diffusion-based generative models for robotics
  • Proven track record of developing multi-modal perception systems integrating tactile, visual, language and other contextual sensing for intelligent robotic agents
  • Strong publication record in robot learning, demonstrating innovative approaches to trust calibration, contextual learning, and generative robotic skill learning

Bonus Points For

  • Research contributions to foundation models and diffusion methods in robotics
  • Experience with large-scale machine learning model development, particularly generative and diffusion-based approaches
  • Expertise in human-in-the-loop learning, correction-based training paradigms, and diffusion-guided skill transfer
  • Demonstrated ability to translate theoretical machine learning research, especially diffusion and generative models, into practical robotic implementations

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