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Job Description

This Machine Learning Engineer role supports mission-focused CV/ML solutions and synthetic data generation for GEOINT. The position is based in Herndon, VA and requires an active U.S. Government TS/SCI clearance to work on classified systems.

Role Summary

As a Machine Learning Engineer at Vantor Services Inc., you will design and deploy core components for computer vision pipelines, build synthetic data generation capabilities using generative AI for GEOINT data, and contribute to production-grade ML and data engineering.

Responsibilities

  • Design, develop, and deploy multiple CV pipeline components, including image preprocessing, distributed training, inference engines, and data stores.
  • Implement synthetic data generation capabilities using generative AI applied to commercial and government GEOINT data.
  • Perform data engineering work to transform multiple data types to support different stages of the AI/ML workflow.
  • Stay current with recent computer vision advances from industry and academia and apply relevant techniques to customer mission problems.
  • Provide internal teams with updates on delivery progress, evaluation results, and project challenges.

Required Qualifications

  • US citizenship and a current TS/SCI clearance, with willingness to obtain a CI Polygraph.
  • 5+ years of programming experience using at least one general purpose language such as Python, Typescript, Java, or C/C++.
  • 2+ years of experience leading design or architecture work for new and existing systems, including design patterns, reliability, and scaling.
  • 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 and AI models using a modern ML framework.
  • Experience deploying machine learning models to 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 using Kubernetes to orchestrate data or ML workflows.
  • 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.

Preferred Qualifications

  • Hands-on experience with LLMs, AI agents, or agentic workflows.
  • Experience working 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.

Technologies

Python, Typescript, Java, C/C++, generative AI, modern ML framework, Kubernetes, CI/CD, infrastructure-as-code, cloud platform, managed compute, databases, storage, identity and access management, LLMs, and AI agents.

Security Clearance Requirement

This position requires an active U.S. Government security clearance at the TS/SCI level.

Location

Herndon, VA (onsite)

Compensation

USD 165,000 - 215,000 per year.

Pay transparency: The base pay for this position within California, Colorado, Hawaii, New Jersey, the Washington, DC metropolitan area, and for all other states is $165,000.00 - $215,000.00.

Benefits

  • Robust 401(k) with company match
  • Mental health resources
  • Student loan repayment assistance
  • Adoption reimbursement
  • Pet insurance

Position Details

  • Title: Machine Learning Engineer (TS/SCI)
  • Company: Vantor Services Inc.
  • Minimum Experience: 5 years
  • Education: Bachelor’s degree in a relevant discipline (as specified)

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