---
title: 'Applied Machine Learning Engineer at Quartermaster'
canonical: 'https://feeny.ai/job/applied-machine-learning-engineer-quartermaster-arlington-8gxjb58ahjjf'
type: 'job'
last_seen: '2026-10-28'
---

# Applied Machine Learning Engineer at Quartermaster

- **Company:** Quartermaster
- **Location:** Arlington, VA
- **Compensation:** $200k–$235k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-09-24
- **Last confirmed live:** 2026-10-28
- **Apply:** https://jobs.ashbyhq.com/quartermaster/f21444da-48fd-492c-aa11-21eacf379b05

## Job description

## About Us

Quartermaster is building the world's most comprehensive maritime intelligence platform. Our SmartMast™ system transforms commercial and civilian vessels into a persistent, distributed sensing network—combining HD video, AI, radar, RF sensing, and AIS to deliver real-time maritime domain awareness at global scale. With 600+ sensors deployed across 25+ countries and more than 400,000 vessels identified outside of AIS, we are setting a new standard for what ocean surveillance and safety can look like. We are a mission-driven, high-velocity team building dual-use technology for defense agencies, coast guards, and commercial maritime operators.

Job Description 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.
- Must be eligible to obtain/maintain a security clearance.

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 production environments.
- 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

- Flexible working hours with occasional deadlines requiring high availability.
- Opportunity to work on innovative projects with a global impact.

## About Quartermaster

## Company Overview
- **One-liner**: Quartermaster builds a real-time, distributed maritime awareness network by equipping vessels with AI-powered sensor packages (SmartMast) and an analytics platform.
- **Entity Type**: Private (Series A)
- **Headquarters**: Arlington, Virginia, United States
- **Founded**: 2023
- **Founders**: Neil Sobin (CEO)

## Core Business
- **Primary industry**: Maritime intelligence, defense technology, AI/robotics, ocean sensing
- **Target customers**: Governments (navies, coast guards), commercial shipping operators, insurers, and maritime researchers (B2G, B2B)
- **Mission**: “Connect every vessel on the water to create a comprehensive, real-time picture of our oceans, unlocking critical data insights that underpin a prosperous global maritime ecosystem.” [quartermaster.us](https://www.quartermaster.us/about)

## Products & Services
- **SmartMast**: A weather-hardened hardware package (cameras, radios, sensors) mounted on a ship’s mast that continuously collects and relays maritime data. Combined with an AI analytics platform, it provides real-time vessel identification, anomaly detection, and environmental monitoring. [techcrunch.com](https://techcrunch.com/2026/05/20/this-startup-raised-43m-to-build-a-hive-mind-for-ships/)
- **Quartermaster Analytics Platform**: Cloud-based software that ingests SmartMast data and applies computer vision and machine learning to generate actionable intelligence for fleet operators, insurers, and government agencies.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: $43 million in Series A funding (announced May 20, 2026) [techcrunch.com](https://techcrunch.com/2026/05/20/this-startup-raised-43m-to-build-a-hive-mind-for-ships/)
- **Notable Investors/Partners**: Co-led by First Round Capital and Quiet Capital, with participation from TMV, Steel Atlas, BoxGroup, Operator Partners, Shorewind Capital, and David (surname not specified). Key hires from Anduril (Steve Ribaudo as CGO) and Scale AI (Matt Beck as COO). [quartermaster.us](https://www.quartermaster.us/about) | [linkedin.com](https://www.linkedin.com/company/quartermasterai)
- **Growth Signals**:
  - Headcount grew 625% year-over-year to 40 employees (as of mid-2026). [linkedin.com](https://www.linkedin.com/company/quartermasterai)
  - Over 600 ships equipped with SmartMast, covering 10 million square miles of ocean. [techcrunch.com](https://techcrunch.com/2026/05/20/this-startup-raised-43m-to-build-a-hive-mind-for-ships/)
  - Assisted in “over 20 rescues of mariners at sea.” [techcrunch.com](https://techcrunch.com/2026/05/20/this-startup-raised-43m-to-build-a-hive-mind-for-ships/)
  - Operates in 7 countries (Panama, Colombia, South Korea, UAE, Brazil, Taiwan, United States). [linkedin.com](https://www.linkedin.com/company/quartermasterai)

## Competitive Advantages
- **Proprietary hardware edge**: SmartMast is far more advanced than the standard AIS (Automatic Identification System), which is opt-in and easily spoofed. Quartermaster’s sensors provide persistent, verified, real-time data that is less susceptible to fraud. [techcrunch.com](https://techcrunch.com/2026/05/20/this-startup-raised-43m-to-build-a-hive-mind-for-ships/)
- **Pro-mariner incentive model**: Rather than selling sensors to fleet operators (a tough sell in a low-margin industry), Quartermaster creates value for mariners (e.g., rescue support, safety data) to encourage voluntary adoption, locking in network effects. [techcrunch.com](https://techcrunch.com/2026/05/20/this-startup-raised-43m-to-build-a-hive-mind-for-ships/)
- **First-mover in distributed ocean sensing**: No other company has deployed a real-time, AI-powered sensor constellation at this scale, giving Quartermaster a data moat and early relationships with governments and commercial fleets.

## Strategic Focus
- **Engineering hiring**: A large portion of the $43M Series A is earmarked for hiring engineers (RF, software, AI, systems) to accelerate product development. [techcrunch.com](https://techcrunch.com/2026/05/20/this-startup-raised-43m-to-build-a-hive-mind-for-ships/)
- **Fleet expansion**: Continue equipping more vessels with SmartMast, especially in key maritime corridors, to densify the network.
- **New applications**: Developing uses for government intelligence, marine autonomy training data, environmental monitoring, and insurance risk assessment.
- **Global presence**: Scaling operations in Latin America, Asia, and the Middle East (already in 7 countries). [linkedin.com](https://www.linkedin.com/company/quartermasterai)

## Why Work Here
- **High-impact mission**: Directly contribute to ocean safety, security, and sustainability – work that has tangible real-world results (e.g., rescues at sea).
- **Fast-growing startup**: 625% YoY headcount growth; employees have significant ownership and influence over product direction.
- **Engineering culture**: “A single engineer can make a significant impact in relatively short periods of time” because the ocean space is largely untapped. [techcrunch.com](https://techcrunch.com/2026/05/20/this-startup-raised-43m-to-build-a-hive-mind-for-ships/)
- **Remote-friendly**: Some roles (e.g., “Opportunity Hire”) are listed as remote, though the HQ in Arlington, VA likely expects hybrid for core engineering teams. [quartermaster.us](https://www.quartermaster.us/jobs/opportunity-hire)
- **Diverse, inclusive environment**: Equal opportunity employer that encourages individuals of all backgrounds to apply. [quartermaster.us](https://www.quartermaster.us/jobs/opportunity-hire)
- **Notable perks**: Not explicitly listed, but the company emphasizes pro-mariner values and a collaborative, mission-driven culture.

## Sources
1. [quartermaster.us/about](https://www.quartermaster.us/about)
2. [techcrunch.com](https://techcrunch.com/2026/05/20/this-startup-raised-43m-to-build-a-hive-mind-for-ships/)
3. [linkedin.com/company/quartermasterai](https://www.linkedin.com/company/quartermasterai)
4. [quartermaster.us/jobs/opportunity-hire](https://www.quartermaster.us/jobs/opportunity-hire)
5. [jobs.ashbyhq.com/quartermaster](https://jobs.ashbyhq.com/quartermaster)

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