SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Tutor Intelligence builds AI robotics systems deployed into real-world facilities. This role focuses on building perception systems that make robot manipulation reliable and effective.
You will own a significant vision system end-to-end: from problem definition and data collection through evaluation, integration, and ongoing improvement on physical robots. The work combines camera geometry and learned models, with all decisions grounded in measured performance on actual hardware.
Key responsibilities include:
- Define technical approaches and success criteria for ambiguous perception problems in robot manipulation
- Build and integrate capabilities such as detection, segmentation, tracking, object pose estimation, and 3D scene understanding
- Own camera calibration, coordinate transforms, synchronization assumptions, and sensor quality checks
- Create reproducible datasets and evaluations covering changes in objects, lighting, viewpoint, and occlusion
- Select and adapt geometric methods and learned models based on accuracy, latency, robustness, and operational constraints
- Deploy and maintain perception in the robot stack; diagnose failures using recorded data and physical experiments
- Improve shared evaluation tools and documentation; mentor colleagues in your domain
You will work closely with research, software, mechanical, and electrical engineers to understand failures across sensing, algorithms, and the robot environment. The company values technical excellence, collaboration, and ownership—engineers make tradeoffs explicit and help colleagues do better work.
Success looks like establishing reproducible baselines and meaningful evaluations for perception problems, delivering measured improvements that hold up on physical robots while meeting runtime constraints, and keeping systems diagnosable and usable through reliable calibration checks and documentation.
Note: All R&D roles at Tutor carry the title "Member of Technical Staff (MoTS)" internally, with level determined through the interview process. The company hires for flexibility and impact rather than fixed org slots.
Requirements:
- Evidence of independently owning a substantial computer-vision system from an ambiguous problem through tested integration
- Strong Python engineering and experience writing maintainable code, tests, and reproducible experiments
- Practical command of camera models, calibration, coordinate frames, and 3D geometry
- Experience with geometric vision or learned visual models, with judgment to explain when each approach is appropriate
- Ability to build representative evaluations, isolate failure modes, and distinguish model improvements from data or measurement artifacts
- Ability to communicate technical tradeoffs and resolve interfaces with engineers in other disciplines
Nice to have:
- Perception deployed on physical robots, especially manipulation systems
- Multi-camera or depth systems, sensor fusion, SLAM, or object pose estimation
- OpenCV, Open3D, or PCL; a modern deep-learning framework; C++ or GPU optimization
