Applied Machine Learning Engineer

About the role

Quartermaster is seeking a versatile Applied Machine Learning Engineer to develop and deploy AI models for its edge‑intelligent maritime systems. You will work across computer vision, sensor fusion, and multi‑modal inference to deliver robust, real‑time solutions for maritime domain awareness.

Key responsibilities

• Design, train, and evaluate models for object detection, classification, anomaly detection, and sensor‑based inference.
• Optimize model architectures and inference pipelines for embedded/edge hardware under compute and bandwidth constraints.
• Develop dataset pipelines, including data augmentation, synthetic data generation, and domain adaptation.
• Implement real‑time processing pipelines on‑device and in cloud environments.
• Create tools for benchmarking, visualization, and debugging of ML performance.

Required profile

• Master’s or PhD in Computer Vision, Machine Learning, Robotics, or related field (Bachelors considered case‑by‑case).
• 4+ years of experience building and deploying ML models in production.
• Eligibility to obtain/maintain a security clearance.

Required skills

• Python programming.
• Deep learning frameworks such as PyTorch or TensorFlow.
• Experience with edge or embedded ML deployments, model compression, and hardware‑aware optimization.
• Working with diverse data types: images, time‑series, geospatial, RF.
• Knowledge of computer vision, signal processing, and multi‑modal fusion techniques.