Machine Learning Engineer, Detection and Tracking

You will own the detection and tracking models that power Helsing's products — training, tuning, and deploying models against US-specific datasets. This is an applied ML role: you won't be writing research papers, but you will be expected to have strong intuition for model performance, data quality, and the practical trade-offs involved in getting detection and tracking systems to work reliably in production. You will manage the full model lifecycle — from assessing and curating training data through annotation, training, evaluation, and deployment to edge platforms.

The day-to-day responsibilities include:

• Training and fine-tuning detection models (YOLO, DETR, Faster R-CNN, and similar architectures) on mission-specific datasets.
• Implementing and improving multi-object tracking pipelines (SORT, DeepSORT, ByteTrack, or similar).
• Evaluating model performance: analyzing metrics, diagnosing failure modes, and iterating on data and model improvements.