$115K – $170K/yr
Senior Research Engineer, Humanoid Manipulation
Role overview
Job description
Advance Humanoid Manipulation Research and Development
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Design, implement, and evaluate learning-based manipulation models and strategies for humanoid robots across a wide range of tasks.
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Drive projects from early concepts through on-robot testing and deployment.
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Develop loco-manipulation capabilities that integrate perception, control, and planning.
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Contribute to foundation models for manipulation, working on model architecture, data collection, large-scale training pipelines, and deployment infrastructure.
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Ensure model development supports generalization and transfer across diverse robotic platforms.
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Collaborate with research scientists to integrate large-scale manipulation data into learning pipelines powering foundation models.
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Train and evaluate manipulation models using imitation learning, reinforcement learning, and other training approaches.
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Translate research ideas into reliable robotic systems that operate in real-world conditions.
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Ensure systems are robust, reproducible, and aligned with data collection and learning objectives.
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Develop experimental infrastructure to support rapid iteration, large-scale training, and evaluation.
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Partner with mechanical and electrical engineers on hardware integration and system bring-up.
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Work closely with field teams to refine interfaces and improve manipulation performance.
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Act as a connective layer between autonomy research and applied robotics engineering.
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Prototype quickly, run experiments on hardware, and validate results in the field.
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Balance exploratory research with concrete deliverables that support near-term goals.
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Debug complex system-level issues spanning software, hardware, data, training infrastructure, and learning.
Drive Robotics Foundation Model Development
Build Systems That Bridge Research and Deployment
Collaborate Across Disciplines
Rapidly Iterate and Deliver
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Bachelor’s, Master’s, or PhD in Robotics, Computer Science, Mechanical Engineering, or a related field.
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2+ years of hands-on experience in robotic manipulation and/or robot learning in academic or industry settings.
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Strong foundation in robot kinematics, dynamics, and control, with a focus on manipulation.
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Strong background in learning-based manipulation, with an emphasis on reinforcement learning and imitation learning, and experience training modern deep-learning models.
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Experience using frameworks such as PyTorch and building reproducible model-training and evaluation pipelines.
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Proven experience implementing and evaluating robotic systems on real hardware.
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Ability to work effectively in fast-paced, highly collaborative environments.
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Curiosity, ownership, and the confidence to challenge assumptions and propose new approaches.
Experience working with humanoid robots or multi-fingered robotic hands.
Experience training large-scale robot foundation models.
Experience with reinforcement-learning fine-tuning, offline RL, and related policy training methods.
Familiarity with large-scale data collection, spanning simulation, web-scale data, human-in-the-loop data, and autonomously-collected data.
Publications or open-source contributions in top robotics or machine-learning venues.
Experience with large-scale robotics data collection and dataset management.
Strong interest in bridging cutting-edge research with field-ready robotic systems.
About this listing
- Source: FieldAI's official careers site (via Lever) · last confirmed on the source 27 Oct 2026
- Posted 2 Sept 2026
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What they are looking for
Skills & requirements
Qualification
What You Have Bachelor’s, Master’s, or PhD in Robotics, Computer Science, Mechanical Engineering, or a related field
Department · Engineering
Hiring company
FieldAI
FieldAI is the leader in deploying general-purpose robots in unstructured environments, providing a universal brain that works across many robots, and many tasks.
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