Machine Learning Engineer (TS/SCI)

Vantor•Herndon, VA

14d•$165,000 - $215,000•Onsite

About The Position

Vantor is hiring a Machine Learning Engineer to develop capabilities for mission-critical problems involving geospatial intelligence (GEOINT) data. The role designs, builds, and deploys computer vision (CV) pipeline components, develops synthetic data generation using generative AI, and engineers data for AI/ML workflows. The engineer keeps up with advances in computer vision and applies them to customer missions, while briefing internal teams on delivery progress, evaluation results, and project challenges. Applicants must be U.S. citizens and hold an active TS/SCI U.S. Government security clearance; willingness to obtain a CI polygraph is required. Employment in cleared roles depends on verification of clearance status. Some roles may also be subject to U.S. export control laws and require U.S. person status. The position offers a base salary of $165,000 to $215,000. Vantor describes its total rewards package as including a 401(k) with company match, mental health resources, student loan repayment assistance, adoption reimbursement, and pet insurance. The application window is three days from the posting date and the role remains posted until a qualified candidate is identified.

Requirements

U.S. citizenship and a current TS/SCI clearance; willingness to obtain a CI polygraph.
At least 5 years of programming experience with at least one general-purpose language, such as Python, TypeScript, Java, C, or C++.
At least 2 years leading the design or architecture of new and existing systems, including design patterns, reliability, and scaling.
At least 2 years of relevant experience in machine learning engineering, data engineering, backend software engineering, or a closely related technical role.
Hands-on experience training, fine-tuning, or adapting machine learning or AI models using a modern ML framework.
Experience deploying ML models into production, including building batch or real-time inference pipelines and managing model versions.
Hands-on experience building and operating services on a major cloud platform, including managed compute, databases, storage, and identity and access management.
Experience building and operating workflow orchestration using Kubernetes for data or ML pipelines.
Experience owning containers, container orchestration, CI/CD pipelines, and infrastructure-as-code.
Ability to support production systems, including debugging, observability, secure configuration, and incident response.
Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, Machine Learning, or a related discipline, or equivalent demonstrated experience.

Nice To Haves

Hands-on experience with LLMs, AI agents, or agentic workflows.
Experience with satellite or aerial imagery, including raster formats such as GeoTIFF, coordinate reference systems, and tools such as GDAL, Rasterio, Shapely, Fiona, and GeoPandas.
Experience developing computer vision models for object detection, semantic or instance segmentation, or change detection, ideally applied to overhead imagery.

Responsibilities

Design, develop, and deploy computer vision pipeline components, such as image preprocessing, distributed training, inference engines, and data stores.
Implement synthetic data generation capabilities using generative AI applied to commercial and government GEOINT data.
Transform various data types through data engineering to support phases of the AI/ML workflow.
Stay current on computer vision advances from industry and academia and apply them to customer mission problems.
Brief internal Vantor teams on delivery progress, evaluation results, and project challenges.