Edge ML Engineer — Real-Time Maritime AI & Sensor Fusion

Quartermaster; Arlington (VA); On-site; USD 120,000 - 170,000; Full time

Job summary

Quartermaster is seeking a versatile Applied ML Engineer to contribute across machine learning and perception tasks powering our edge‑intelligent maritime systems. You will work with computer vision, sensor fusion, and lightweight inference pipelines to deliver robust AI solutions for harsh field conditions.

Collaborate with hardware, software, and product teams to ship production models, optimize for embedded hardware, and iterate rapidly on experiments.

Qualifications

• Master’s or PhD in Computer Vision, ML, Robotics (Bachelor’s considered case-by-case).
• 4+ years of production ML experience.
• Proficient in Python and DL frameworks (PyTorch, TensorFlow).
• Experience with edge/embedded ML deployments and model compression.
• Strong debugging, experimentation, and problem-solving skills.
• Excellent collaboration and communication across teams.

Responsibilities

• Design, train, and evaluate models for object detection, classification, and sensor-based tasks.
• Optimize inference pipelines for embedded/edge hardware.
• Contribute to dataset labeling, augmentation, and domain adaptation.
• Prototype across AI subfields including CV, signal processing, and multi-modal fusion.
• Implement real-time pipelines for processing sensor data on-device and in the cloud.
• Develop tools for benchmarking, visualization, and debugging.

Skills

Python

PyTorch

TensorFlow

Edge AI

Computer Vision

Sensor fusion

Education

Master's or PhD in Computer Vision/ML/Robotics

Bachelor's considered on case-by-case

Tools

Docker

ONNX

CUDA

Job description

Quartermaster is seeking a versatile Applied ML Engineer to contribute across machine learning and perception tasks powering our edge‑intelligent maritime systems. You will work with computer vision, sensor fusion, and lightweight inference pipelines to deliver robust AI solutions for harsh field conditions.

Collaborate with hardware, software, and product teams to ship production models, optimize for embedded hardware, and iterate rapidly on experiments.