Robotics Lead

Location: Bay Area

About Autolane

Autolane is on a mission to revolutionize last-mile logistics by empowering autonomous vehicle owners to unlock the value of their vehicle. Our flagship product is the industry's first orchestration layer for autonomous deliveries—coordinating heterogeneous autonomous systems (AVs, humanoid robots, delivery bots) to achieve zero-wait handoffs and maximum fleet utilization. We integrate directly with retailers, commercial real-estate operators, and AV fleets, building the robotics infrastructure that enables autonomy at scale.

The Role

As Robotics Lead at Autolane, you'll architect and build the multi-robot systems that execute autonomous last-mile logistics. Starting with Unitree G1 humanoid integration for order loading and expanding to PUDU delivery bot coordination, you'll design the motion planning, manipulation, and multi-robot orchestration systems that bridge the gap between AI decision-making and physical execution.

You'll work directly with our CTO to build robotics systems that scale from pilot deployments to coordinated fleets of humanoids and delivery bots operating across retail environments nationwide.

Core Responsibilities

Humanoid Robot Integration (Unitree G1)

• Motion Planning: Design and implement manipulation pipelines for order loading—grasp planning, trajectory optimization, and collision avoidance
• Locomotion Control: Develop robust walking and navigation for retail environments including curbs, ramps, and dynamic obstacles
• Task Choreography: Build loading sequences coordinating G1 movements with vehicle trunk access, order verification, and secure placement
• Sensor Integration: Fuse RGB-D cameras, force/torque sensors, and proprioceptive feedback for adaptive manipulation
• Safety Systems: Implement human-aware motion planning and emergency stop behaviors for shared spaces

Multi-Robot Coordination

• Fleet Architecture: Design distributed coordination systems for heterogeneous robot types (G1 humanoids, PUDU bots, future platforms)
• Task Allocation: Build real-time task assignment integrating with the AI/ML orchestration layer's MARL policies
• Spatial Deconfliction: Implement multi-robot path planning preventing collisions and deadlocks in shared operating zones
• Handoff Protocols: Design robot-to-vehicle and robot-to-robot transfer sequences with verification and fallback behaviors
• State Synchronization: Maintain consistent world models across distributed robot systems

ROS2 Platform Development

• System Architecture: Design modular ROS2 architecture with clean separation between perception, planning, and control
• Navigation Stack: Customize Nav2 for retail environments—dynamic costmaps, behavior trees, and recovery behaviors
• MoveIt2 Integration: Configure manipulation pipelines for G1 arm control with custom kinematics and planning plugins
• micro-ROS Bridge: Architect communication between ROS2 nodes and embedded edge sensors
• DDS Optimization: Tune middleware for low-latency, high-reliability messaging in production deployments

Simulation & Testing Infrastructure

• Digital Twins: Build high-fidelity simulation environments in Isaac Sim for G1 and delivery bot development
• Physics Validation: Ensure sim-to-real transfer for manipulation, locomotion, and contact dynamics
• Scenario Testing: Design automated test suites covering nominal operations and edge cases
• Hardware-in-the-Loop: Integrate real robot subsystems with simulated environments for incremental validation
• Continuous Integration: Build CI/CD pipelines for robotics code with simulation-based regression testing

Production Robotics Systems

• Reliability Engineering: Design for 99.9% uptime in outdoor retail environments
• Remote Operations: Build teleoperation fallbacks and remote monitoring dashboards
• Diagnostics & Logging: Implement comprehensive observability for field debugging and performance analysis
• OTA Updates: Architect safe over-the-air deployment for robot software across distributed fleets
• Fleet Management: Build tooling for robot provisioning, configuration, and health monitoring

Required Qualifications

Technical Foundation

• 5+ years robotics engineering with production deployment experience
• Expert proficiency in C++ and Python for robotics systems
• Deep expertise with ROS2 architecture, lifecycle management, and production deployment
• Strong foundation in motion planning algorithms (sampling-based, optimization-based, learning-based)
• Hands-on experience with manipulation systems—grasp planning, trajectory optimization, force control
• Proven ability to take robots from prototype to reliable production operation

Core Robotics Competencies

• Proven experience with mobile robot navigation—SLAM, localization, path planning
• Working knowledge of robot kinematics, dynamics, and control theory
• Strong foundation in sensor fusion and state estimation (EKF, particle filters, factor graphs)
• Ability to design and debug complex real-time systems with deterministic timing requirements

Production & Infrastructure Skills

• Experience building robotics CI/CD pipelines with simulation-based testing
• Strong understanding of ROS2 middleware, DDS configuration, and network optimization
• Knowledge of containerization (Docker) and deployment orchestration for robot fleets
• Proven ability to build observable, debuggable robotics systems in production environments

AI Development Fluency

• Active daily use of AI coding assistants (Claude Code, Cursor, GitHub Copilot) for robotics development
• Demonstrated ability to leverage LLMs for rapid prototyping, debugging, and documentation
• Experience using AI tools for test generation and code review

Preferred Qualifications

Advanced Robotics Experience

• Humanoid robots (Unitree, Boston Dynamics, Agility) or complex manipulation platforms
• Legged locomotion control and whole-body motion planning
• Dexterous manipulation with multi-fingered hands or adaptive grippers
• Behavior trees for complex task sequencing and error recovery
• Contact-rich manipulation and force-controlled assembly tasks
• Human-robot interaction in shared workspaces

Platform Experience

• Unitree SDK and G1-specific development
• PUDU or similar delivery bot platforms
• MoveIt2 advanced configuration and custom plugin development
• Nav2 customization for complex environments
• Isaac Sim or Gazebo for physics-based simulation
• Foxglove or custom visualization for robot debugging

Domain Experience

• Logistics or warehouse robotics deployments
• Retail or hospitality robot operations
• Multi-robot systems at scale (10+ robots)
• Outdoor robotics with environmental challenges
• Fleet management and remote operations

Research & Innovation

• Publications in top robotics venues (ICRA, IROS, RSS, CoRL)
• Experience translating research into production systems
• Open-source contributions to ROS2, MoveIt2, Nav2, or simulation tools
• Familiarity with latest advances in foundation models for robotics and manipulation

Our Robotics Innovation Culture

At Autolane, we're building the physical execution layer for autonomous logistics—combining cutting-edge robotics with AI to create systems that act intelligently in the real world:

• Rapid Prototyping: Move from simulation to real-robot validation in days with hardware arriving continuously
• AI-Augmented Development: Use LLMs to accelerate ROS2 development, behavior design, and debugging
• Real-World Impact: Your robots will execute actual autonomous deliveries in production environments
• Cross-Functional Innovation: Collaborate with ML engineers, embedded systems, and operations teams
• Research-to-Production: Bridge the gap between academic robotics and deployed systems

Why Join Our Robotics Team?

• Cutting-Edge Hardware: Work with Unitree G1 humanoids, delivery bots, and next-gen platforms as they arrive
• Direct Impact: Your systems will physically execute millions of autonomous deliveries
• Technical Leadership: Work directly with CTO and Head of R&D on architectural decisions
• Growth Trajectory: Build the robotics foundation as we scale from pilots to nationwide deployment
• Innovation Freedom: Experiment with novel manipulation strategies, locomotion approaches, and coordination algorithms
• Mission-Critical Work: Build the robotics systems that make autonomous logistics physically possible

Working Environment & Requirements

• Location: Portland strongly preferred for hardware lab access; exceptional remote candidates considered
• Hardware Lab: Access to Unitree G1, PUDU bots, motion capture, and prototyping equipment
• Compute Resources: GPU workstations for simulation, GCP infrastructure for fleet systems
• Field Testing: Regular deployment to pilot sites (Stanford Shopping Center, Barton Creek Mall)
• Collaboration: Direct partnership with CTO on architecture decisions
• Pace: Fast-moving startup environment where shipping working robots matters

Interview Process Note:

Be prepared to:

• Walk through robotics systems you've designed and deployed to production
• Demonstrate your AI-augmented development workflow for ROS2 and simulation
• Discuss trade-offs in motion planning approaches (when to use sampling vs optimization vs learning)
• Show examples of designing manipulation pipelines and grasp strategies
• Explain how you'd approach coordinating humanoids and delivery bots for order handoffs
• Describe system architecture decisions you've made for reliable robot deployments

Bonus points for:

• Showing working robot demos or production deployments
• Metrics from deployed robotics systems (uptime, task success rate, cycle time)
• Experience with humanoids or complex manipulation platforms
• Creative solutions to sim-to-real transfer, contact dynamics, or outdoor operation challenges
• ROS2 packages or open-source contributions
• Real-world deployments involving multi-robot coordination or logistics