Research Scientist, Dexterous Manipulation & Robot Learning

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

About LILA

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.

We’re All In

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.