Applied Machine Learning Engineer

The role

The Applied Machine Learning Engineer will design, train, and evaluate models for object detection, classification, and anomaly detection. This role involves optimizing model architectures for embedded hardware and implementing real-time pipelines for sensor data.

What you will do

• Design, train, and evaluate models for object detection, classification, anomaly detection, and sensor-based inference.
• Optimize model architectures and inference pipelines for performance on embedded/edge hardware.
• Contribute to dataset development and labeling strategy.
• Support prototyping and experimentation in computer vision, signal processing, and multi-modal fusion.
• Implement real-time pipelines for processing sensor data on-device and in cloud environments.
• Develop tools and scripts for benchmarking, data visualization, and debugging ML model performance.
• Stay current with machine learning research and tools.
• Participate in code reviews, team knowledge sharing, and internal technical documentation.

Required qualifications

• Must be eligible to obtain/maintain a security clearance.

Nice to have

• Master’s or PhD in Computer Vision, Machine Learning, Robotics, or related field.
• Bachelors candidates considered on a case by case basis.
• 4+ years of experience building and deploying machine learning models in production environments.
• Proficiency in Python and experience with deep learning frameworks such as PyTorch or TensorFlow.
• Comfortable working with a range of data types (images, time-series, geospatial, RF, etc.).
• Experience with edge or embedded ML deployments, including model compression and hardware-aware optimization.
• Familiarity with common ML practices including cross-validation, hyperparameter tuning, and model monitoring.
• Excellent debugging, experimentation, and problem-solving skills.
• Strong collaboration and communication skills with both technical and non-technical team members.
• experience in maritime, aerospace, or other remote sensing domains.

Benefits

• Flexible working hours with occasional deadlines requiring high availability.
• Opportunity to work on innovative projects with a global impact.

Before you apply

• Must be eligible to obtain/maintain a security clearance.

About the company

Quartermaster is building a maritime intelligence platform using the SmartMast system. The company builds dual-use technology for defense agencies, coast guards, and commercial maritime operators.