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Embedding VC

Early-stage venture fund for Generative AI

Senior / Staff Robotics Engineer - Motion Planning

Robotics & Autonomous SystemsConfirmed live in the last 24 hours
Full-timeMilpitas, CA, USA

About the Job

Requirements

  • A Ph.D. in Robotics, Mechanical Engineering, Computer Science, or a related field, or an M.S. degree with 4+ years of relevant industry experience.
  • Deep hands-on experience developing and tuning advanced local planners and trajectory optimization algorithms for mobile robots in complex, unstructured environments.
  • Strong understanding of kinematics, vehicle dynamics, and center-of-mass constraints for top-heavy mobile robots operating on uneven outdoor terrain.
  • Expertise in modern C++ (C++17/20), with strict attention to real-time performance, memory management, and low-latency execution; comfortable bridging high-latency AI outputs with hard real-time control loops.
  • Proven track record of building and deploying autonomous navigation stacks on real, physical robotic platforms in the wild.
  • Requires five days per week of in-office collaboration with the teams.

Responsibilities

  • Architect and implement advanced local planners, such as optimization-based approaches like MPC, MPPI, or custom contouring control, that translate AI-generated routes into trajectories a heavy, non-holonomic base can physically execute on uneven terrain.
  • Build high-performance C++ pipelines that ingest the AI team's neural network outputs, including semantic maps and learned costmaps, in real time and convert them into deterministic mathematical constraints for the planner.
  • Ensure local planners dynamically adjust to real-time changes in the robot's center of mass caused by the lifting column and dual-arm payloads; make trajectories guarantee stability and prevent tipping on slopes or rough ground.
  • Build the deterministic C++ safety layer and fallback behaviors that override AI inputs if a commanded path violates physical safety constraints or off-the-shelf SLAM tracking drops.
  • Architect local planning interfaces to pass base trajectories, velocity limits, and dynamic constraints to the upcoming Whole-Body Control architecture, bridging base mobility and upper-body manipulation.

Desired Qualifications

  • Familiarity with Whole-Body Control frameworks, operational space control, and how mobile bases synchronize with high-degree-of-freedom manipulators.
  • Experience tuning, debugging, or filtering outputs from commercial SLAM/VIO systems when they fail in visually degraded environments.
  • Background in detecting slip or loss of traction from proprioceptive sensor signals and adapting planning constraints accordingly.
  • Experience using CUDA to accelerate grid processing or trajectory sampling pipelines.

About the Company

Embedding VC

Early-stage venture fund for Generative AI

Embedding VC is an early-stage venture fund that backs Generative AI startups. It provides seed to early-stage capital and operational guidance, leveraging a team of current and former builders and operators who can help portfolio companies grow. The fund’s approach centers on working closely with founders and using hands-on experience to scale AI projects, including those aiming toward AGI, during a period described as a new computing super cycle driven by AI innovations. Unlike funds that rely mainly on financial leverage, Embedding VC differentiates itself through its deep operator network, practical support, and focus on and commitment to building capable, scalable AI businesses. The overall goal is to support ambitious AI founders to advance the development and deployment of AI technologies and capture value in the expanding AI ecosystem.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Menlo Park, CA
Founded
2023

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