Edge ML Engineer — Computer Vision & Object Tracking

Motion Recruitment; Arlington, Northern (VA, KY); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Motion Recruitment is seeking a senior applied machine learning engineer to join a high-performing CV team in Arlington. You will develop and deploy object detection and multi-object tracking models across real-world applications, owning the full ML lifecycle from data curation to production deployment.

You will optimize models for edge hardware and work with TensorRT/ONNX to meet latency and compute constraints.

Qualifications

• 5+ years of professional experience in applied machine learning or computer vision.
• Bachelor’s degree in Computer Science, Electrical Engineering, or related field; Master’s/PhD valued.
• Proven experience deploying object detection models in production environments.
• Strong Python programming with PyTorch or similar framework.
• Deep understanding of CV datasets, annotation quality, training behavior, and evaluation metrics.
• Experience end-to-end ML lifecycle: data, annotation, training, evaluation, optimization, deployment.

Responsibilities

• Develop, train, and fine-tune object detection models (YOLO, DETR, Faster R-CNN).
• Build and improve multi-object tracking pipelines (SORT, DeepSORT, ByteTrack).
• Evaluate model performance, analyze failures, and propose improvements.
• Own data and model pipeline: data curation, annotation coordination, augmentation, training, validation.
• Optimize models for edge/embedded hardware balancing speed, accuracy, and compute.
• Collaborate with software/systems teams to integrate CV models into production.

Skills

Python programming

PyTorch

Object detection / CV

Multi-object tracking

Edge deployment

Model evaluation

MLOps basics

Education

Bachelor's degree in Computer Science/EE

Tools

TensorRT

ONNX

CUDA

CVAT / Label Studio

Job description

Motion Recruitment is seeking a senior applied machine learning engineer to join a high-performing CV team in Arlington. You will develop and deploy object detection and multi-object tracking models across real-world applications, owning the full ML lifecycle from data curation to production deployment.

You will optimize models for edge hardware and work with TensorRT/ONNX to meet latency and compute constraints.