Applied ML Engineer

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October 22

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Quartermaster

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Artificial Intelligence • Cybersecurity • Transport

Quartermaster is a company redefining maritime intelligence by providing unmatched precision and visibility in real-time to monitor the world's most remote waters. Their AI-powered SmartMast system transforms everyday vessels into a comprehensive ocean intelligence network, significantly enhancing the monitoring of maritime activities and addressing issues such as smuggling and illegal fishing. By leveraging onboard sensors and high-bandwidth satellite connectivity, Quartermaster delivers high-resolution detections and actionable insights to users, ensuring enhanced maritime awareness and decision-making.

2 - 10 employees

Founded 2023

🤖 Artificial Intelligence

🔒 Cybersecurity

🚗 Transport

📋 Description

• Design, train, and evaluate models for tasks ranging from object detection and classification to anomaly detection and sensor-based inference • Optimize model architectures and inference pipelines for performance on embedded/edge hardware under compute and bandwidth constraints • Contribute to dataset development and labeling strategy, including data augmentation, synthetic data generation, and domain adaptation • Support prototyping and experimentation across a variety of AI subfields, including 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 the latest research and tools in machine learning and evaluate their applicability to our product roadmap • Participate in code reviews, team knowledge sharing, and internal technical documentation

🎯 Requirements

• 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 • 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 • Bonus: experience in maritime, aerospace, or other remote sensing domains

🏖️ Benefits

• Competitive salary • Flexible work hours and the option for remote work. • Opportunities for professional development and continued education.