Machine Learning Engineer

Responsibilities

• Train and fine-tune detection models on mission-specific datasets
• Implement and improve multi-object tracking pipelines
• Evaluate model performance, diagnose failure modes, and iterate on data and model improvements
• Manage data pipelines including raw-data assessment, annotation coordination, dataset curation, and augmentation
• Optimize models for SWaP-constrained and embedded platforms through quantization, pruning, TensorRT, and ONNX export
• Collaborate with systems engineers to integrate models into the Altra platform
• Work across electro-optical, infrared, and other imaging sensor modalities

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
• Proficiency in Python and PyTorch or a comparable deep learning framework
• Experience with data curation, annotation management, training, evaluation, and deployment across the full model lifecycle
• Experience optimizing models for SWaP-constrained and edge platforms using techniques such as TensorRT, ONNX, and quantization
• Practical understanding and implementation experience with multi-object tracking algorithms
• Ability to read and apply scientific computer vision papers 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 is preferred
• Experience with infrared or thermal imaging and multiple sensor modalities is preferred
• Familiarity with MLflow, Weights & Biases, dataset versioning, and model registries is preferred
• Experience with CVAT, Label Studio, or similar annotation tools is preferred
• Computer vision experience in segmentation, pose estimation, or activity recognition is preferred
• Experience with simulators, emulators, or synthetic data generation is preferred
• Experience deploying models on GPU-accelerated embedded platforms such as NVIDIA Jetson is preferred
• Background in defense, intelligence, or other mission-critical environments is preferred

Benefits

• Medical and travel insurance coverage
• Flexible paid time off
• Paid holidays
• Remote and/or hybrid work available depending on position
• Generous compensation and benefits package