Real-Time Embedded Computer Vision Engineer

SR2 | Socially Responsible Recruitment | Certified B Corporation™; United States; On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Health, dental, vision and life ins.

Vacation and sick leave

401(k) and commuter benefits

Job summary

SR2 | Socially Responsible Recruitment | Certified B Corporation is seeking expert Machine Learning Engineers with deep experience in computer vision and deployment on low-cost embedded systems. You will design, train, and optimize real-time DL models for resource-constrained hardware, leveraging quantization, pruning, and hardware acceleration.

The role spans multiple levels from mid to staff/lead, offering challenging projects in embedded vision and edge AI across ARM, Jetson, and Qualcomm

Qualifications

• 5+ years in ML, DL, and CV.
• Experience deploying optimized DL models.
• Proficiency with Python and C++.
• Familiar with embedded platforms.
• Background in hardware acceleration.

Responsibilities

• Design and optimize CV models for real-time embedded systems.
• Apply quantization, pruning, and distillation for performance.
• Deploy ML models on ARM/NVIDIA Jetson/Qualcomm hardware.
• Write clean Python/C++ code with TensorFlow, PyTorch, ONNX.
• Develop SLAM, object detection, tracking, feature extraction.
• Collaborate with teams to integrate ML into production.
• Benchmark and profile models for latency and power.
• Research cutting-edge ML techniques for real-time performance.

Skills

Machine Learning

Deep Learning

Computer Vision

Python

C++

TensorFlow

PyTorch

ONNX

TensorRT

Model Quantization

Embedded Systems

Education

Master's degree

PhD

Tools

TensorFlow

PyTorch

ONNX

TensorRT

CUDA

OpenCL

Job description

SR2 | Socially Responsible Recruitment | Certified B Corporation is seeking expert Machine Learning Engineers with deep experience in computer vision and deployment on low-cost embedded systems. You will design, train, and optimize real-time DL models for resource-constrained hardware, leveraging quantization, pruning, and hardware acceleration.

The role spans multiple levels from mid to staff/lead, offering challenging projects in embedded vision and edge AI across ARM, Jetson, and Qualcomm