Machine Learning Engineer, Detection and Tracking

Who we are  

Helsing develops artificial intelligence-enabled capabilities to protect and defend democracies. We build Altra, an AI-powered drone software platform, and HX-2, our autonomous drone. We are growing our US operations, cultivating an ambitious and committed team of mission-driven professionals to apply their skills to solve challenging problems.  

The role  

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  

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  

Managing the data pipeline end-to-end: assessing raw data, coordinating annotation, curating datasets, and implementing augmentation strategies  

Optimizing models for deployment on SWaP-constrained and embedded platforms (quantization, pruning, TensorRT, ONNX export)  

Collaborating with systems engineers to integrate models into the broader Altra platform  

Working across sensor modalities as needed, including electro-optical, infrared, and other imaging sources  

You should apply if you  

Have 5+ years of experience in applied machine learning or computer vision  

Have a Bachelor's degree in Computer Science, Electrical Engineering, or a related field; Master's or PhD strongly preferred  

Have production experience training and deploying object detection models — not just research or academic projects  

Are proficient in Python and PyTorch or a comparable deep learning framework  

Have strong intuition for data quality; you can look at annotated datasets, training curves, and evaluation metrics and know what's wrong  

Have experience with the full model training lifecycle: data curation, annotation management, training, evaluation, and deployment  

Have experience optimizing models for deployment on SWaP-constrained and edge platforms (TensorRT, ONNX, quantization)  

Understand multi-object tracking and have implemented or worked with tracking algorithms in practice  

Can read and contextualize scientific papers in computer vision and apply findings to production systems  

U.S. citizenship required  

Nice to have  

Strong proficiency in Rust or C++ for production model deployment and optimization  

Experience with multiple sensor modalities — particularly infrared or thermal imaging  

Familiarity with MLOps tooling: experiment tracking (MLflow, Weights & Biases), dataset versioning, model registries  

Experience with annotation tools and workflows (CVAT, Label Studio, or similar)  

Background in computer vision beyond detection — segmentation, pose estimation, activity recognition  

Experience with simulators, emulators, or synthetic data generation for training and evaluation  

Experience deploying models on GPU-accelerated embedded platforms (NVIDIA Jetson, similar)  

Background in defense, intelligence, or other mission-critical environments  

Join Helsing and work with world-leading experts in their fields  

Helsing’s work is important. You’ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns

The work is unique. We operate in a domain that has highly unusual …