Robotics AI / Application Layer Engineer (AMR + Manipulation + Teleoperation)

About the Company

APEX is a Silicon Valley–based robotics startup building humanoid robots to automate labor-intensive and repetitive jobs across industries.

We are currently offering part-time, in-person roles for individuals who want to gain hands-on experience in real-world robotics development. This is an opportunity to work closely with our engineering team on cutting-edge robotics systems.

This position is ideal for 
students or recent graduates
 who are eager to build practical experience in robotics, AI, and hardware systems.

Location Requirement:
 This is an in-person role. Applicants must currently reside in the Bay Area.

About the Role

We are looking for a Robotics AI / Application Layer Engineer to build the intelligence layer of our robotic systems, focusing on 
autonomous mobile robots (AMRs), robotic arms, and humanoid manipulation systems
.

You will be responsible for implementing and deploying advanced AI policies, teleoperation pipelines, and navigation systems that bring real-world robotic systems to life.

This role sits at the intersection of 
robot learning, computer vision, and real-world robotics deployment
.

Key Responsibilities1. Teleoperation & Robot Learning Pipelines

• Build and maintain teleoperation pipelines using 
  LeRobot and Hugging Face ecosystems
• Implement data collection systems for robotic manipulation tasks
• Support imitation learning workflows from human demonstrations
• Integrate real-time control interfaces for robotic arms and humanoids

2. Model Deployment for Robotic Manipulation

• Deploy trained manipulation models on real robotic arms
• Implement and optimize 
  diffusion policy models
   for robot control
• Ensure robust sim-to-real transfer of learned policies
• Optimize inference latency for real-time execution on edge hardware

3. AMR Navigation & SLAM Systems

• Implement SLAM-based navigation systems for indoor AMR operation
• Work with LiDAR, depth cameras, and IMU data fusion
• Develop path planning and obstacle avoidance pipelines
• Integrate navigation stack with robot task planning systems

4. Robot Intelligence & Application Layer

• Design high-level behavior logic for autonomous robot tasks
• Integrate perception, planning, and control into unified pipelines
• Work closely with hardware and systems engineers to ensure full-stack functionality
• Support deployment, testing, and iteration in real-world environments

Required Skills & Experience

• Strong experience in 
  Python and robotics software development
• Experience with 
  ROS2 (or ROS1), Gazebo, Isaac Sim, or equivalent
• Hands-on experience with:
• SLAM (2D/3D)
• Robot navigation stacks (Nav2 or similar)
• Computer vision or sensor fusion
• Familiarity with 
  robot learning / imitation learning / reinforcement learning
• Experience with deep learning frameworks (PyTorch preferred)
• Understanding of robotic manipulation or mobile robotics systems

Preferred / Bonus Skills

• Experience with 
  diffusion policies for robotics
• Experience using 
  Hugging Face / LeRobot / open robotics datasets
• Experience with robotic arms (UR, Franka, or custom manipulators)
• Experience deploying models on edge devices (Jetson, NVIDIA platforms)
• Familiarity with teleoperation systems and human-in-the-loop control
• Experience in simulation-to-real-world transfer

What You’ll Work On

• Building real-world autonomous robotic systems (AMRs + arms)
• Deploying state-of-the-art robot learning models into production
• Enabling robots to learn from human demonstrations
• Creating navigation and manipulation systems for indoor environments

Why This Role Matters

You will be directly responsible for the 
intelligence layer of our robotics platform
, turning perception, learning, and control algorithms into real-world autonomous behavior.

This is a high-impact role with direct influence on product performance in real environments.