Data Scientist – Edge AI & Embedded Systems

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: This project is going to span the full data and model life-cycle, and you're going to get to flex different parts of your skillsets across the project. Here are some examples of tasks and responsibilities that you may have: 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. Experience analyzing RF or signal data; familiarity with Software Defined Radios (SDRs). Understanding of modern digital communication systems, including RF, cellular, and WiFi. Experience with MLOps practices such as model versioning and experiment tracking in offline environments. Ability to communicate complex technical topics to a range of audiences, including technical and non-technical leaders. Pay Transparency: To support pay transparency, Vantor includes salary ranges in all U.S. job postings. Starting pay for this role will fall within the listed range and will be based on factors such as experience, qualifications, skills, location, and market conditions. Candidates who meet the minimum requirements for the role should not expect to receive compensation at the top of the range. The listed range reflects the expected pay for this position, and final offers will be determined based on each candidate’s experience, expertise, and alignment with the role. ● The base pay for this position within the Washington, DC metropolitan area is: $140,000.00 - $187,000.00 - $205,700.00 annually. For all other states, we use geographic cost of labor as an input to develop market-driven ranges for our roles, and as such, each location where we hire may have a different range. Benefits: Vantor offers a competitive total rewards package that goes beyond the standard, including a robust 401(k) with company match, mental health resources, and unique perks like student loan repayment assistance, adoption reimbursement and pet insurance to support all aspects of your life. You can find more information on our benefits at: The application window is three days from the date the job is posted and will remain posted until a qualified candidate has been identified for hire. If the job is reposted regardless of reason, it will remain posted three days from the date the job is reposted and will remain reposted until a qualified candidate has been identified for hire. The date of posting can be found on Vantor's Career page at the top of each job posting. To apply, submit your application via Vantor's Career page. EEO Policy: Vantor is an equal opportunity employer committed to an inclusive workplace. We believe in fostering an environment where all team members feel respected, valued, and encouraged to share their ideas. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability, protected veteran status, age, or any other characteristic protected by law.