Data Scientist - Edge AI & Embedded Systems

maxar; Reston (VA); On-site; USD 120,000 - 160,000; Full time

Job summary

Vantor in Reston, VA is seeking an experienced AI/ML engineer to join a small team delivering edge AI capabilities for DoD customers. You will source data, train models, evaluate performance, and deploy optimized solutions on embedded hardware in air-gapped environments. U.S.

citizenship and TS/SCI clearance with CI poly are required. Strong Python/Linux skills and experience with Docker are essential. You will work onsite with mission operators to ensure the system meets real-world operational

Qualifications

• Bachelor's degree or higher in a technical field such as data science, CS, CE, statistics, or electrical engineering.
• At least five years of relevant experience.
• U.S. Citizen with TS/SCI clearance and CI poly.
• Strong knowledge of AI/ML algorithms including computer vision models and LLMs; hands-on training and evaluation with PyTorch or TensorFlow.
• Proficiency in Python and its data science stack (NumPy, pandas, scikit-learn) plus Bash scripting.
• Experience configuring Linux applications and deploying offline-native applications with Docker.

Responsibilities

• Source, curate, clean, and label datasets from open-source repositories and operational sensor data.
• Train, fine-tune, and evaluate AI/ML models, including computer vision models and LLMs, for specific mission use cases.
• Design evaluation methods and metrics to measure model accuracy, latency, and reliability under real-world conditions.
• Optimize models for resource-constrained hardware using techniques such as quantization, pruning, and conversion to edge runtimes.
• Build and deploy offline-native data and ML pipelines in containerized environments using Docker.
• Configure and troubleshoot Linux-based embedded systems, including compatibility between specific kernels and hardware drivers.
• Explore and analyze data from digital communication systems, including RF, cellular, and WiFi sources.
• Evaluate open-source AI software and models to identify solutions that meet the customer's operational requirements.
• Engage with customers to understand expectations and ensure delivered products meet operational requirements.
• Produce supporting documentation, including model performance reports and inputs for user manuals.

Skills

AI/ML algorithms

Computer vision models

LLMs

PyTorch

TensorFlow

Python

NumPy

pandas

scikit-learn

Bash scripting

Education

Bachelor's degree in data science / CS / engineering

Tools

Docker

GitHub

GitLab

Hugging Face

Kaggle

TensorRT

ONNX Runtime

Job description

Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what's happening now and shape what's coming next. Vantor is a place for problem solvers, changemakers, and go-getters-where people are working together to help our customers see the world differently, and in doing so, be seen differently. Come be part of a mission, not just a job, where you can: Shape your own future, build the next big thing, and change the world.

To be eligible for this position, you must be a U.S. Citizen. This position requires an active U.S. Government security clearance, applicants who do not currently hold the required clearance will not be eligible for consideration. Employment for cleared roles is contingent upon verification of clearance status.

Export Control/ITAR: Certain roles may be subject to U.S. export control laws, requiring U.S. person status as defined by 8 U.S.C. 1324b(a)(3).

Please review the job details below.

This position requires an active U.S. Government Security Clearance at the TS/SCI level with CI Polygraph.

Project Description. Working as part of a small team of highly knowledgeable and skilled experts, you are helping the customer bring modern AI/ML capabilities to the tactical edge. Your team will take this project from concept to completion - identifying use cases; sourcing and curating data; recommending existing open-source, COTS, and GOTS models and applications; training, fine-tuning, and evaluating models; deploying them onto embedded hardware in air-gapped environments; and then sending out for use. We need someone who is curious, detail-oriented, loves digging into data and finding solutions to challenging problems, is as comfortable analyzing model performance as troubleshooting a Linux driver on a single board computer, and can communicate these complex concepts to less technical decision makers.

Location

This is an on-site position, reporting daily to work in Reston, VA. You will be working alongside your customer, the mission operators, and the requirements owners.

Responsibilities

• Source, curate, clean, and label datasets from open-source repositories (GitHub, GitLab, Hugging Face, Kaggle) and operational sensor data.
• Train, fine-tune, and evaluate AI/ML models, including computer vision models and LLMs, for specific mission use cases.
• Design evaluation methods and metrics to measure model accuracy, latency, and reliability under real-world conditions.
• Optimize models for resource-constrained hardware using techniques such as quantization, pruning, and conversion to edge runtimes.
• Build and deploy offline-native data and ML pipelines in containerized environments using Docker.
• Configure and troubleshoot Linux-based embedded systems, including compatibility between specific kernels and hardware drivers.
• Explore and analyze data from digital communication systems, including RF, cellular, and WiFi sources.
• Evaluate open-source AI software and models to identify solutions that meet the customer's operational requirements.
• Engage with customers to understand expectations and ensure delivered products meet operational requirements.
• Produce supporting documentation, including model performance reports and inputs for user manuals.

Minimum Qualifications

• Bachelor's degree or higher in an applicable technical degree, such as data science, computer science, computer engineering, statistics, or electrical engineering.
• At least five years of relevant experience.
• U.S. Citizen with a TS/SCI clearance and CI poly.
• Solid understanding of AI/ML algorithms, including computer vision models and LLMs, and hands-on experience training and evaluating models using frameworks such as PyTorch or TensorFlow.
• Proficiency in Python and its data science ecosystem (e.g., NumPy, pandas, scikit-learn), plus Bash scripting.
• Experience configuring and building applications in Linux and deploying offline-native applications with Docker.

Preferred Qualifications

• Previous experience working on-site to support the DoD or the IC.
• Experience with data preparation, including cleaning, labeling, augmentation and managing datasets.
• Awareness of the current open-source AI/ML landscape and familiarity with GitHub, GitLab, Hugging Face, and Kaggle.
• Contributions to open-source projects.
• Experience optimizing models for edge deployment (quantization, pruning, TensorRT, ONNX Runtime, llama.cpp).
• Familiarity with embedded system design and troubleshooting low-level Linux issues.
• Understanding of common hardware architectures, including x86, ARM, SoC, and RISC-V.
• Experience with any Single Board Computer (SBC), including Raspberry Pi, Arduino, BeagleBoard, NVIDIA Jetson, etc.
• Experience with lower-level languages such as C, C++, or Java.