PCRecruiter - Recruitment Software & Applicant Tracking System
AI Embedded Systems Engineer
PCRecruiter - Recruitment Software & Applicant Tracking System - New York, New York, us, 10261
Work at PCRecruiter - Recruitment Software & Applicant Tracking System
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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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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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