CX2 is seeking a highly skilled Robotics Integration Engineer to join our growing team.
This role requires an onsite presence in our El Segundo, CA HQ; a remote work environment is not considered for this opportunity.
Key Responsibilities
Integrate sensors, onboard compute, and distributed robotics subsystems across perception, control, logging, and ML workflows
Design and maintain reliable data pipelines, middleware interfaces, and communication frameworks for distributed robotic systems operating over high-latency or constrained networks.
Optimise system performance across CPU, GPU, memory, storage, and network resources
Build robust networking solutions for unreliable, bandwidth-constrained, or multi-robot environments
Deploy and maintain software on embedded and edge platforms using reproducible environments, containerisation, and CI/CD workflows
Implement observability, testing, and validation tools to support debugging, field testing, and operational reliability
Ensure systems degrade gracefully under high load, intermittent connectivity, or partial failure conditions
Required Qualifications
Core
Strong programming skills in C++ and/or Python
Experience with containerization and DevOps practices for robotics (e.g., Docker, CI/CD)
Experience with Linux systems programming
Solid understanding of networking fundamentals, including transport protocols, latency, throughput, and reliability trade-offs.
Experience with robotics middleware and communication frameworks, such as ROS/ROS2, DDS-based systems, or modern pub/sub alternatives.
Experience integrating and working with real hardware systems (beyond simulation)
Familiarity with embedded platforms (e.g., NVIDIA Jetson, FPGA, RTOS)
Strong understanding of concurrency, memory management, performance-critical system design
Experience profiling and optimizing systems (e.g., perf, Valgrind, tracing tools)
Robotics / Systems
Performance Engineering
Bonus Points
Hands-on experience with multicopter drones and their autopilot systems (e.g., PX4, ArduPilot)
Experience with simulations stacks such as Isaac Sim or Gazebo
High-throughput data (video, radar, RF/IQ streams)
Zero-copy and shared memory techniques
GPU pipelines (CUDA, TensorRT)
Edge-to-cloud architectures
Knowledge of time synchronization (PTP, NTP, clock drift handling) and distributed systems design patterns
Exposure to: SLAM / perception pipelines and ML inference systems in production
ITAR Regulations
What We Offer