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Applied Machine Learning Engineer

quartermasterArlington, VAEngineering
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Salary
$200K – $235K
Job type
Full-time
Experience
Senior · 4+ yrs
Posted
24 Sept 2026
Status
Open · checked 8d ago

About this role

Based in Arlington, VA, the Applied Machine Learning Engineer position at Quartermaster involves building edge-intelligent maritime systems and perception tasks. This role suits professionals with experience in production machine learning environments who want to work on maritime intelligence technology.

Role Overview

Quartermaster seeks an Applied Machine Learning Engineer to handle machine learning and perception responsibilities for maritime intelligence platforms. The employee will build lightweight inference pipelines, work on computer vision and sensor fusion, and fine-tune models in production alongside cross-functional engineering teams.

Key Responsibilities

Build, train, and assess models for object detection, classification, anomaly detection, and sensor-based inference.
Tune model architectures and inference pipelines for embedded and edge hardware under bandwidth and compute limits.
Build dataset strategies encompassing data labeling, synthetic data generation, domain adaptation, and data augmentation.
Support experimentation and prototyping across multi-modal fusion, signal processing, and computer vision.
Construct real-time pipelines for processing sensor data in cloud environments and on-device.
Build utilities and scripts for debugging, data visualization, and benchmarking model results.
Review research and tools in machine learning to determine utility for the product roadmap.
Engage in technical documentation, code reviews, and knowledge sharing.
Maintain or obtain eligibility for a security clearance.

Requirements

Experience building and deploying machine learning models in production environments.
Knowledge of Python and deep learning frameworks like TensorFlow or PyTorch.
Experience handling diverse data types including geospatial, time-series, images, and RF data.
Background in edge or embedded ML deployments, including hardware-aware optimization and model compression.
Understanding of ML techniques such as model monitoring, cross-validation, and hyperparameter tuning.
Debugging, problem-solving, and collaboration capabilities.
Eligibility to obtain or maintain a security clearance.

Nice to Have

Master's or PhD degree in Robotics, Machine Learning, Computer Vision, or a related field, though Bachelor's candidates are evaluated individually.
Experience in remote sensing, aerospace, or maritime domains.

Skills and Tools

Python
PyTorch
TensorFlow
Computer Vision
Sensor Fusion
Edge and Embedded ML
Signal Processing
Multi-modal Fusion

Salary and Benefits

Salary range between $200K and $235K
Equity offerings included
Flexible working hours

About the Company

Quartermaster creates a maritime intelligence platform that uses the SmartMast system to convert civilian and commercial vessels into a sensing network. The company combines AIS, radar, AI, HD video, and RF sensing to provide real-time maritime domain awareness for commercial operators, coast guards, and defense agencies globally.

How to Apply

Candidates should visit the official Quartermaster careers page to submit an application for this role.

Skills and tech stack

PythonPyTorchTensorFlowComputer VisionDeep LearningMachine LearningFine-tuning

Questions candidates ask

What is the location of the job?

The job is located in Arlington, VA.

What is the salary and compensation structure?

The salary ranges from $200K to $235K and includes equity offers.

What education level is required?

A Master's or PhD in Machine Learning, Computer Vision, Robotics, or a related field is preferred, but Bachelor's candidates are evaluated on a case-by-case basis.

How many years of experience are needed?

The posting specifies 4+ years of experience building and deploying machine learning models in production environments.

Are there any special clearance requirements?

Applicants must be eligible to obtain and maintain a security clearance.

Ready to apply?

The application is on the official quartermaster careers page.

Apply on company site