Bear Robotics
Senior Robotics Engineer
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Job Title: Senior Robotics Engineer
Department: Robotics Software Engineering
The Computer Vision Engineer will develop and deploy perception systems for manipulation and mobile robotics, working across model development, sensor integration, data, evaluation and runtime optimization, and partnering closely with robot-learning and controls engineers to turn visual predictions into dependable action.
Key Duties/Responsibilities
Perception Systems Development
- Develop vision systems for object detection, segmentation, tracking, pose estimation, depth, scene understanding, and task-state recognition.
- Build perception capabilities that support grasping, manipulation, navigation, human awareness, and closed-loop robot behavior.
- Select and adapt modern architectures, including transformer-based, multimodal, open-vocabulary, and foundation-model approaches where they provide practical value.
Data & Evaluation
- Create and improve datasets through collection, annotation, synthetic generation, augmentation, active learning, and disciplined failure mining.
- Design offline and on-robot evaluation that measures accuracy, calibration, robustness, latency, and downstream task impact across representative conditions.
Sensor Integration & Deployment
- Integrate cameras and depth sensors; address calibration, synchronization, coordinate transforms, noise, and hardware-specific failure modes.
- Optimize models and pipelines for real-time inference on robot compute while maintaining useful accuracy and predictable resource use.
- Deploy perception components into the robot software stack with strong logging, monitoring, fallback behavior, and regression coverage.
Problem Solving & Troubleshooting
- Diagnose field and lab failures systematically and turn recurring edge cases into data, model, or systems improvements.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Collaboration & Communication
- Collaborate with robot learning, controls, simulation, hardware, and product teams throughout development and pilot validation.
- Performs other duties or takes on specialized responsibilities as assigned.
Supervisory Responsibilities
None
Required Skills/Abilities/Qualifications
- Strong practical experience developing computer-vision or multimodal perception systems beyond classroom projects.
- Excellent Python skills and substantial experience with PyTorch or an equivalent deep-learning framework.
- Good knowledge of modern vision methods in several relevant areas, such as detection, segmentation, tracking, pose estimation, depth, or representation learning.
- Experience building datasets, training models, selecting metrics, and performing structured error analysis.
- Understanding of camera geometry, calibration, coordinate systems, and the relationship between perception outputs and physical-world decisions.
- Ability to write production-quality code and integrate models into larger software systems with appropriate tests and observability.
- Strong experimental judgment and the persistence to resolve performance gaps caused by data, models, sensors, or deployment conditions.
- Clear communication and effective collaboration across AI, robotics, and hardware disciplines.
Preferred Skills/Abilities/Qualifications
- Perception for robotic manipulation, mobile robots, autonomous systems, or other embodied-AI applications.
- 6D object pose estimation, visual servoing, grasp perception, articulated-object understanding, or hand-object interaction.
- RGB-D, stereo, event cameras, LiDAR, or multi-camera systems.
- Open-vocabulary perception, vision-language models, self-supervised learning, or multimodal foundation models.
- Synthetic data, domain randomization, simulation, and sim-to-real transfer.
- CUDA, TensorRT, ONNX, or other inference optimization and profiling tools.
- ROS/ROS 2 and deployment on embedded or edge GPU hardware.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Education/Experience
- A degree in computer science, machine learning, robotics, engineering, or a related field, or equivalent practical experience.
- At least three years' relevant work experience.
Physical Requirements
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
- Prolonged periods of sitting/standing at a desk and working on a computer. The employee routinely is required to sit; stand, walk; talk and hear; use hands to keyboard.
- Specific vision abilities required by this job include close vision, color vision, peripheral vision, depth perception, and ability to adjust focus.
- Ability to lift 30 lbs.
- Occasional travel to partner or pilot sites may be required.
Bear Robotics, Inc. is proud to be an Equal Opportunity Employer. We do not discriminate on the basis of race, color, ancestry, national origin, religion or religious creed, mental or physical disability, medical condition, genetic information, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, gender expression, age, marital status, military or veteran status, citizenship, or other characteristics protected by state or federal law or local ordinance.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location