AI Embedded Systems Engineer

Title: Edge AI Systems Engineer – Autonomous Robotics

Location: Manhattan, NY (Hybrid or On-Site)

About the Company:

A trailblazing force in intelligent automation is seeking an Edge AI Systems Engineer to help shape the future of smart robotics. With applications spanning from advanced manufacturing to cutting-edge healthcare systems, this innovator combines machine learning and embedded computing to build autonomous platforms that thrive in dynamic, real-world environments. Join a team where engineering creativity meets mission-driven purpose, and make a tangible impact on the next generation of adaptive robotics.

Position Summary:

This role is perfect for an engineer with deep expertise in both embedded systems and AI deployment who wants to push the boundaries of real-time robotic intelligence. As an Edge AI Systems Engineer, you’ll build high-performance software and hardware integration pipelines, ensuring neural networks execute with precision, speed, and safety on resource-constrained platforms.

Key Responsibilities:

• Develop and optimize embedded software that powers intelligent edge devices across robotic platforms.
• Translate ML models into real-time, deployable code using frameworks like TensorRT and ONNX.
• Design and implement low-level drivers for sensors, actuators, and control systems.
• Integrate sensor fusion and computer vision algorithms for onboard decision-making.
• Tune systems for low latency and high reliability in safety-critical, real-world applications.
• Collaborate cross-functionally with AI, hardware, and robotics teams for end-to-end deployment.
• Perform hardware bring-up, integration testing, and diagnostics for prototype systems.

Technology Environment:

• Languages: C/C++, Python
• Platforms: NVIDIA Jetson, ARM Cortex-M, STM32, Coral Edge TPU
• Tools & Frameworks: TensorRT, ONNX, RTOS, ROS2, Yocto, PyTorch, TensorFlow Lite, OpenCV
• Interfaces: CAN, I2C, SPI

Qualifications:

Required:

• BS or MS in Electrical Engineering, Computer Engineering, Robotics, or a related field.
• 3+ years of experience developing firmware for embedded systems with AI integration.
• Proven experience deploying neural networks to edge platforms or hardware accelerators.
• Strong skills in real-time software optimization and debugging on embedded targets.
• Knowledge of sensor technologies, control loops, and system-level integration.

Preferred:

• Hands-on experience with robotic vision systems, depth sensors, or lidar.
• Background in signal processing or real-time sensor fusion.
• Familiarity with safety compliance standards in automation or robotics (e.g., ISO 13849).
• Exposure to model optimization methods such as quantization and pruning.

What’s Offered:

• Direct impact on product design and deployment in intelligent automation systems.
• Competitive compensation package with equity opportunities.
• Robust benefits including health coverage and professional development support.
• Hands-on access to emerging tools in AI, robotics, and edge computing.
• A collaborative engineering culture driven by innovation and experimentation.