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Research Scientist, Dexterous Manipulation & Robot Learning
Lila Sciences · Cambridge, MA USA · Active · $176,000–$304,000 / year · Greenhouse
Job facts
| Field | Value |
|---|---|
| Company | Lila Sciences |
| Title | Research Scientist, Dexterous Manipulation & Robot Learning |
| Normalized title | - |
| Department / team | Robotics |
| Location | Cambridge, MA, United States |
| Work model | - |
| Employment type | - |
| Salary | $176,000–$304,000 / year |
| Status | active |
| ATS provider | Greenhouse |
| Posted / first seen | 2025-12-22 / 2026-05-29 |
| Changed / last seen | 2026-05-29 / 2026-06-22 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Lila Sciences. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Greenhouse. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in Cambridge. | Open |
| Department jobs | Active postings in Robotics. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Lila Sciences |
| Source | a1e67975-fd33-4f8d-940f-2dbc2480c450 |
| ATS provider | Greenhouse |
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
Compensation
We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.
International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Expected Base Salary Range $176,000 — $304,000 USD 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.
Full job record
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| Board ID | a1e67975-fd33-4f8d-940f-2dbc2480c450 |
| Provider | greenhouse |
| Provider Job Key | 4087170009 |
| Title | Research Scientist, Dexterous Manipulation & Robot Learning |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Cambridge, MA USA |
| Department | Robotics |
| Team | — |
| Employment Type | — |
| Workplace Type | — |
| Remote Policy | — |
| Country | United States |
| Region | MA |
| City | Cambridge |
| Salary Raw | Salary Range $176,000 — $304,000 USD About LILA Lila Sciences is building Scientific Superintel |
| Salary Min | 176,000 |
| Salary Max | 304,000 |
| Salary Currency | USD |
| Salary Period | year |
| Source URL | https://job-boards.greenhouse.io/lilasciences/jobs/4087170009 |
| Apply URL | https://job-boards.greenhouse.io/lilasciences/jobs/4087170009 |
| First Seen At | 2026-05-29 23:01:25Z |
| Last Seen At | 2026-06-22 07:42:50Z |
| Last Checked At | 2026-06-22 07:42:50Z |
| Last Changed At | 2026-05-29 23:01:25Z |
| Inactive At | — |
| Source Posted At | 2025-12-22 20:26:20Z |
| Source Updated At | 2026-05-14 21:07:24Z |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=lilasciences/date=2026-06-22/2026-06-22T07-42-50-532Z-2e9b2ea5c360f7de6fdb22575bfbe763aec37d4dd651384d405921b5db11b39e.json |
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