Research Scientist, Dexterous Manipulation & Robot Learning (AI/Robotics)

TL;DR

Research Scientist, Dexterous Manipulation & Robot Learning (AI/Robotics): Leading the research and development of autonomous robotic systems for a scientific superintelligence platform with an accent on precise and dexterous manipulation using foundation models and reinforcement learning. Focus on developing novel human-robot interaction frameworks and advancing multi-modal sensing for intelligent robotic agents.

Location: Cambridge, MA USA

Salary: $176,000–$304,000 USD per year

Company

hirify.global is the world’s first scientific superintelligence platform and autonomous lab pioneering AI applications in scientific discovery for life, chemistry, and materials science.

What you will do

• Pioneer approaches for precise and dexterous robotic manipulation leveraging foundation models, reinforcement learning, diffusion-based methods, and human guidance.
• Develop novel human-robot interaction frameworks incorporating imitation learning and learning from human guidance, feedback, and demonstrations.
• Advance dexterous manipulation research through cutting-edge machine learning approaches, including diffusion models and adaptive learning algorithms.
• Synthesize multi-modal sensing (tactile, visual, and language) to develop generative skill representations and sophisticated motor learning policies.
• Design autonomous robotic systems with trust calibration mechanisms, enabling dynamic behavior adjustment based on contextual information.

Requirements

• 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, with specific expertise in diffusion-based generative models for robotics.
• Proven track record of developing multi-modal perception systems integrating tactile, visual, and language sensing.
• Strong publication record in robot learning, demonstrating innovative approaches to trust calibration, contextual learning, and generative robotic skill learning.

Nice to have

• 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 into practical robotic implementations.

Culture & Benefits

• Competitive base salary with bonus potential and generous early equity.
• Commitment 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.
• Opportunity to work on solutions for human health, climate, and sustainability.