Edge AI Computer Vision Engineer for Embedded Systems

Envision Technology, LLC.; Manchester (NH); In loco; USD 90.000 - 130.000; Tempo pieno

Descrizione del lavoro

Envision Technology, LLC. is seeking a Computer Vision Engineer – Edge AI to develop and optimize image recognition for embedded systems. You will work on robust CV models, synthetic data generation, and performance validation for mission-critical environments.

The role requires expertise in PyTorch/TensorFlow, OpenCV, and deployment on NVIDIA Jetson or similar hardware, with a strong emphasis on quantitative evaluation and collaboration across engineering teams.

Competenze

• Bachelor’s degree in CS/EE/Math/Physics or related field.
• Proficiency with ML frameworks (PyTorch, TensorFlow, ONNX) and CV libraries (OpenCV).
• Experience deploying models on embedded/edge hardware like Jetson or NUC.

Mansioni

• Assess and optimize image recognition algorithms for embedded/edge devices.
• Create synthetic labeled datasets and physics-based synthetic imagery.
• Quantify model performance with precision, recall, and confusion matrices.
• Collaborate with hardware and software teams to meet mission requirements.
• Stay current with edge AI methods and deployment frameworks.

Conoscenze

PyTorch

TensorFlow

ONNX

OpenCV

NVIDIA TensorRT

OpenVINO

Python

C++

Embedded edge hardware

Quantitative evaluation

Formazione

Bachelor's degree in Computer Science, Electrical Engineering, Applied Mathematics, Physics, or a related field

Master’s degree or 5+ years of experience in applied AI/ML for imaging, optical, or sensor-based systems

Strumenti

Blender

Unreal Engine

Custom rendering pipelines

NVIDIA Jetson

Intel NUC

Descrizione del lavoro

Envision Technology, LLC. is seeking a Computer Vision Engineer – Edge AI to develop and optimize image recognition for embedded systems. You will work on robust CV models, synthetic data generation, and performance validation for mission-critical environments.

The role requires expertise in PyTorch/TensorFlow, OpenCV, and deployment on NVIDIA Jetson or similar hardware, with a strong emphasis on quantitative evaluation and collaboration across engineering teams.