About Quartermaster

At Quartermaster AI, we believe the ocean should be a safe and sustainably managed resource for all. By leveraging cutting-edge AI and robotics, we unlock capabilities that were only recently impossible. Our distributed open-ocean systems enable every vessel to sense, compute, and communicate, enhancing maritime domain awareness for those who need it most.

Equal Employment Opportunity (EEO) Statement

Quartermaster AI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, genetic information, or any other protected status under applicable federal, state, or local laws.

We encourage individuals of all backgrounds to apply and join us in shaping the future of defense technology. If you require accommodations during the application or interview process, please let us know.

We are seeking a versatile and pragmatic Applied ML Engineer to contribute across a broad range of machine learning and perception tasks that power our edge-intelligent maritime systems. This role requires someone comfortable wearing many hats—from working with computer vision and sensor fusion models to building lightweight inference pipelines, designing experiments, and fine-tuning model behavior in production. You’ll work closely with a cross-functional team spanning hardware, software, and product to deliver real-world AI solutions that are robust, efficient, and reliable under challenging field conditions. This is an ideal position for someone who thrives on variety, rapidly shifting problem domains, and turning rough ideas into deployed systems.

Key Responsibilities: 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

Qualifications (Preferred): 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

Work Environment: This is a remote position with collaboration via online tools. Flexible working hours with occasional deadlines requiring high availability. Opportunity to work on innovative projects with a global impact.

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