Search
Go
Machine Learning Engineer, Detection and Tracking
Summary by AIEngineer.careers
Machine Learning Engineer, Detection and Tracking is a Computer Vision Engineer role (full-time). with Helsing. in WASHINGTON, US. Compensation shown: $220K–$292K. Imported listing (source: jobs-radar.com). Apply on the employer's site (jobs-radar.com).
Imported listing (source: jobs-radar.com) · Apply on jobs-radar.com
WASHINGTON · US
$220K–$292K
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from jobs-radar.com
Helsing seeks a Machine Learning Engineer to own detection and tracking models for its AI-powered drone platform. This role involves training, tuning, and deploying models on mission-specific datasets, managing the full model lifecycle from data curation to edge deployment.
Responsibilities
- Training and fine-tuning detection models (YOLO, DETR, Faster R-CNN) on mission-specific datasets
- Implementing and improving multi-object tracking pipelines (SORT, DeepSORT, ByteTrack)
- Evaluating model performance: analyzing metrics, diagnosing failure modes
- Managing data pipeline end-to-end: assessing raw data, coordinating annotation, curating datasets
- Optimizing models for deployment on SWaP-constrained platforms (quantization, pruning, TensorRT, ONNX)
- Collaborating with systems engineers to integrate models into the broader platform
Requirements
- 5+ years experience in applied machine learning or computer vision
- Bachelor's degree in CS, EE, or related field (MS/PhD preferred)
- Production experience training and deploying object detection models
- Proficient in Python and PyTorch
- Experience with full model training lifecycle: data curation, annotation, training, evaluation, deployment
Helsing
München · DE · 900+ employees
Helsing is a defense AI company that provides AI-enabled software and autonomous systems to protect democracies. Its solutions integrate into existing hardware to enhance battlefield awareness and precision across land, air, sea, and electronic warfare domains.
