Machine Learning Engineer (TS/SCI)

Vantor•Herndon, VA

12d•Onsite

About The Position

Vantor is hiring a Machine Learning Engineer to develop solutions for mission-critical problems involving geospatial intelligence (GEOINT) data. The role focuses on creating and deploying computer vision (CV) pipeline components and synthetic data generation capabilities, and on engineering data to support AI/ML workflows. The engineer will track advances in computer vision and apply them to customer mission problems, while briefing internal teams on delivery progress, evaluation results, and project challenges. Applicants must be U.S. citizens and hold an active TS/SCI clearance; employment is contingent on clearance verification. The position also requires willingness to obtain a CI Polygraph. The listed base salary range is $165,000–$215,000, with starting pay determined by job-related factors and work location. The application window is three days from posting and remains open until a qualified candidate is identified.

Requirements

U.S. citizenship and an active TS/SCI clearance, with willingness to obtain a CI Polygraph.
At least 5 years of programming experience with one or more general-purpose languages such as Python, TypeScript, Java, C, or C++.
At least 2 years of experience 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.
Proven 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 multiple 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 varied data types 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.