Embodied AI Robotics Engineer: SLAM, RL & Embedded

Switch Tech Talent; Denver (CO); On-site; USD 130,000 - 190,000; Full time

Job summary

Switch Tech Talent is seeking an Embodied AI Software Engineer to integrate robotics, deep learning, sensor fusion and simulation. You will enable vehicles to understand surroundings, navigate independently and make real-time decisions.

You will develop policies with imitation and reinforcement learning, build SLAM and localisation solutions, and collaborate on sim-to-real workflows for embedded robotic platforms.

Qualifications

• MSc or PhD in Computer Science, Robotics, Electrical Engineering or related discipline.
• Strong production-level C++ programming skills with Python and PyTorch.
• Strong understanding of state estimation and sensor fusion (EKF/UKF, particle filters, factor graphs, VIO or SLAM).
• Experience with localisation, mapping and odometry across visual, LiDAR or multi-sensor systems.
• Experience applying reinforcement learning to robotics or autonomous control.
• Experience taking ML systems from development into real-world robots or autonomous vehicles.

Responsibilities

• Develop deep-learning based driving and manoeuvring policies using imitation and reinforcement learning.
• Build localisation, mapping and SLAM solutions from camera, LiDAR, IMU, wheels and GNSS data.
• Work with NeRFs and 3D Gaussian Splatting to simulate environments and generate sensor data.
• Create sim-to-real workflows and evaluate model performance from simulation to real vehicles.
• Collaborate with robotics, hardware and controls engineers to deploy ML models on embedded robotic platforms.

Skills

Imitation learning

Reinforcement learning

C++

Python

PyTorch

Localization

Sensor fusion

SLAM

Embedded robotics

Education

MSc or PhD in Computer Science, Robotics, Electrical Engineering

Tools

LiDAR

GNSS

IMU

Job description

Switch Tech Talent is seeking an Embodied AI Software Engineer to integrate robotics, deep learning, sensor fusion and simulation. You will enable vehicles to understand surroundings, navigate independently and make real-time decisions.

You will develop policies with imitation and reinforcement learning, build SLAM and localisation solutions, and collaborate on sim-to-real workflows for embedded robotic platforms.