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Machine Learning Engineer, Detection and Tracking

1 month ago
United States
Full-time
Senior
Machine Learning Engineer
Software Development
C++ Computer Vision Generative AI Machine Learning MLflow Python PyTorch Reinforcement Learning Rust
Apply Now
Helsing

Helsing

Helsing is a security and AI company committed to safeguarding democracies through cutting-edge technology, emphasizing ethical standards and global leadership in real-time information processing.

Aerospace & Defense
51-250
Founded 2021
$343M raised
View All Jobs 37

Description

  • Own the detection and tracking models that power Helsing's products.
  • Train, fine-tune, and deploy detection models on mission-specific and US-specific datasets.
  • Implement and improve multi-object tracking pipelines.
  • Evaluate model performance by analyzing metrics, diagnosing failure modes, and iterating on data and model changes.
  • Manage the full data pipeline end-to-end, including raw data assessment, annotation coordination, dataset curation, and augmentation strategies.
  • Optimize models for deployment on SWaP-constrained and embedded platforms using techniques such as quantization, pruning, TensorRT, and ONNX export.
  • Collaborate with systems engineers to integrate models into the broader Altra platform.
  • Work across multiple sensor modalities, including electro-optical, infrared, and other imaging sources.

Requirements

  • 5+ years of experience in applied machine learning or computer vision.
  • Bachelor's degree in Computer Science, Electrical Engineering, or a related field; Master's or PhD strongly preferred.
  • Production experience training and deploying object detection models, not just research or academic projects.
  • Proficiency in Python and PyTorch or a comparable deep learning framework.
  • Strong intuition for data quality and the ability to diagnose issues from annotated datasets, training curves, and evaluation metrics.
  • Experience with the full model training lifecycle, including data curation, annotation management, training, evaluation, and deployment.
  • Experience optimizing models for deployment on SWaP-constrained and edge platforms, including TensorRT, ONNX, and quantization.
  • Understanding of multi-object tracking and practical experience with tracking algorithms.
  • Ability to read and contextualize scientific papers in computer vision and apply findings to production systems.
  • U.S. citizenship with an active security clearance or the ability to obtain one.
  • Strong proficiency in Rust or C++ for production model deployment and optimization (preferred).
  • Experience with multiple sensor modalities, particularly infrared or thermal imaging (preferred).
  • Familiarity with MLOps tooling such as MLflow, Weights & Biases, dataset versioning, and model registries (preferred).
  • Experience with annotation tools and workflows such as CVAT or Label Studio (preferred).
  • Background in computer vision beyond detection, such as segmentation, pose estimation, or activity recognition (preferred).
  • Experience with simulators, emulators, or synthetic data generation for training and evaluation (preferred).
  • Experience deploying models on GPU-accelerated embedded platforms such as NVIDIA Jetson (preferred).
  • Background in defense, intelligence, or other mission-critical environments (preferred).

Benefits

  • A generous compensation and benefits package in addition to base salary.
  • Medical and travel insurance coverage.
  • Flexible paid time off.
  • Paid holidays.
  • Remote and/or hybrid work available depending on the position.
  • A focus on outcomes rather than time-tracking.

Interested in this position?

Apply directly on the company website

Apply Now

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