Senior Robot Learning Engineer – Large Behaviour Models
Bristol (On-site)
Competitive Salary
Full-time, Permanent
We are working with a cutting‑edge robotics company developing advanced humanoid systems for real‑world manipulation tasks. They are seeking a Senior Robot Learning Engineer to lead the development of large behaviour models for complex, bi‑manual robotic manipulation.
This role sits at the intersection of robot learning, foundation models, and real‑world deployment, offering the opportunity to bring state‑of‑the‑art research into production systems.
The Role
You will take ownership of scaling and deploying advanced policy architectures across a humanoid robotics platform, working on:
- Large behaviour models (diffusion, transformer‑based, VLA/VLM)
- Reinforcement learning and imitation learning pipelines
- Multi‑task, language‑conditioned manipulation policies
- Sim‑to‑real transfer and real‑world deployment
Key Responsibilities
- Design, train, and deploy end‑to‑end robot learning models
- Scale diffusion transformer and VLA‑based architectures
- Develop generalisable, multi‑task manipulation policies
- Advance RL pipelines for fine‑tuning beyond imitation learning
- Build sim‑to‑real transfer workflows
- Collaborate across perception, MLOps, and robotics teams
- Contribute to research direction and publish at top‑tier venues
Requirements
- MSc/PhD in ML, Robotics, Computer Science or similar
- Strong experience in robot learning for real‑world systems
- Expertise in at least two of:
- Behaviour cloning
- Diffusion models
- Reinforcement learning
- Vision‑language‑action models
- Strong PyTorch and distributed training experience
- Proven research or applied impact (publications, systems, OSS)
Nice to Have
- Humanoid or bi‑manual manipulation experience
- Sim‑to‑real experience (MuJoCo, Isaac Sim, etc.)
- Experience with CLIP, DINOv2, or similar models
- RL fine‑tuning techniques (residual RL, DPPO, etc.)
Apply Now
#J-18808-Ljbffr”, “datePosted”: “2026-05-20”, “hiringOrganization”: { “@type”: “Organization”, “name”: “American Society of Civil Engineers”, “sameAs”: “https://uk.whatjobs.com/pub_api__cpl__436990998__4861?utm_campaign=publisher&utm_medium=api&utm_source=4861&geoID=22” }, “jobLocation”: { “@type”: “Place”, “address”: { “@type”: “PostalAddress”, “addressLocality”: “Bristol” } } }Senior Robot Learning Engineer – Large Behaviour Models
Bristol (On-site)
Competitive Salary
Full-time, Permanent
We are working with a cutting‑edge robotics company developing advanced humanoid systems for real‑world manipulation tasks. They are seeking a Senior Robot Learning Engineer to lead the development of large behaviour models for complex, bi‑manual robotic manipulation.
This role sits at the intersection of robot learning, foundation models, and real‑world deployment, offering the opportunity to bring state‑of‑the‑art research into production systems.
The Role
You will take ownership of scaling and deploying advanced policy architectures across a humanoid robotics platform, working on:
- Large behaviour models (diffusion, transformer‑based, VLA/VLM)
- Reinforcement learning and imitation learning pipelines
- Multi‑task, language‑conditioned manipulation policies
- Sim‑to‑real transfer and real‑world deployment
Key Responsibilities
- Design, train, and deploy end‑to‑end robot learning models
- Scale diffusion transformer and VLA‑based architectures
- Develop generalisable, multi‑task manipulation policies
- Advance RL pipelines for fine‑tuning beyond imitation learning
- Build sim‑to‑real transfer workflows
- Collaborate across perception, MLOps, and robotics teams
- Contribute to research direction and publish at top‑tier venues
Requirements
- MSc/PhD in ML, Robotics, Computer Science or similar
- Strong experience in robot learning for real‑world systems
- Expertise in at least two of:
- Behaviour cloning
- Diffusion models
- Reinforcement learning
- Vision‑language‑action models
- Strong PyTorch and distributed training experience
- Proven research or applied impact (publications, systems, OSS)
Nice to Have
- Humanoid or bi‑manual manipulation experience
- Sim‑to‑real experience (MuJoCo, Isaac Sim, etc.)
- Experience with CLIP, DINOv2, or similar models
- RL fine‑tuning techniques (residual RL, DPPO, etc.)
Apply Now
#J-18808-Ljbffr…