Blue Signal
Overview
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.
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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.
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