Real-Time SLAM & Spatial AI Engineer

Proception Inc.; Palo Alto (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive salary & meaningful equity

Comprehensive health, dental, vision

Work with world-class researchers in.R

High-ownership role with impact

Pioneering real-world spatial AI

Job summary

Proception Inc. seeks a skilled robotics researcher to design and deploy real-time SLAM and state-estimation systems for humanoid and mobile robots. You will build multi-sensor fusion pipelines, develop neural scene representations, and bridge traditional geometry with learning-based models.

You will enable long-horizon 3D world modeling for manipulation and interaction tasks, integrating perceptions into VLA systems and ensuring robustness in real-world environments.

Qualifications

• MS or PhD in Robotics, CS, CV or related field, or equivalent industry experience.
• Strong background in SLAM, state estimation, and probabilistic sensor fusion.
• Deep understanding of 3D geometry and multi-view geometry.
• Hands-on experience building perception systems for real robotic platforms.
• Experience with neural scene representations such as NeRFs, neural occupancy grids, or implicit SDFs.
• Proficiency in Python and C++ in Linux-based robotics environments.
• Experience with large-scale datasets and long-running perception or learning experiments.
• Self-driven, systems-oriented, and excited about deploying perception on real robots.
• Familiarity with Vision-Language-Action (VLA) or embodied AI systems.
• Experience with tactile, force, or event-based sensors.
• Background in Gaussian splatting, neural SDFs, or hybrid geometric-learning map representations.
• Experience integrating perception outputs into manipulation or control pipelines.
• Familiarity with Isaac Sim, MuJoCo, or photorealistic simulation environments.

Responsibilities

• Design and deploy real-time SLAM and state-estimation systems for humanoid and mobile robots.
• Build multi-sensor fusion pipelines combining RGB-D, stereo, LiDAR, IMU, and tactile sensing.
• Develop neural scene representations including NeRFs, neural occupancy grids, and signed distance fields.
• Bridge classical geometry-based perception with learning-based spatial models.
• Enable long-horizon 3D world modeling for manipulation and interaction tasks.
• Integrate perception outputs into Vision-Language-Action (VLA) systems.
• Improve robustness under occlusion, motion blur, lighting variation, and sensor noise.
• Support sim-to-real transfer using synthetic data generation and domain randomization.
• Collaborate closely with robotics, controls, and learning teams to close the perception-action loop.

Skills

SLAM and state estimation

3D geometry & multi-view geometry

Python & C++ in Linux robotics

Large-scale datasets & long-running ML

Vision-Language-Action familiarity

Neural scene representations (NeRFs)

Perception on real robots

Robotics perception integration with控制

VLA/embodied AI familiarity

Tactile/force sensors

Gaussian splatting / neural SDFs / map

Simulation tools familiarity (Isaac-Si

Education

MS/PhD in Robotics, CV, CS or related field

Tools

Isaac Sim

MuJoCo

Job description

Proception Inc. seeks a skilled robotics researcher to design and deploy real-time SLAM and state-estimation systems for humanoid and mobile robots. You will build multi-sensor fusion pipelines, develop neural scene representations, and bridge traditional geometry with learning-based models.

You will enable long-horizon 3D world modeling for manipulation and interaction tasks, integrating perceptions into VLA systems and ensuring robustness in real-world environments.