Applied AI Engineer

Parsons Corporation•Westminster, CO
•$74,800 - $130,900•Onsite

About The Position

Parsons is looking for an Applied AI Engineer to help build production-grade AI applications that transform complex real-world data into actionable information. This role sits at the intersection of applied AI, computer vision, robotics, geospatial systems, and software engineering. You will work with diverse data sources, including drone imagery and video, mobile and 360° imagery, point clouds, LiDAR, geospatial data, and 3D models, and develop systems that apply modern AI techniques to analyze, organize, and reason over that information. Our work increasingly touches drones, intelligent sensing, and autonomy, particularly where AI can improve how real-world environments are captured, reconstructed, understood, and inspected. This is a hands-on engineering role for someone who enjoys taking ideas from prototype to production. You should be comfortable working across AI models, backend services, data pipelines, and user-facing applications. This role would be based out of Parsons Westminster, Colorado office and will require in-office presence.

Requirements

  • Bachelor's degree in Computer Science, Engineering, Robotics, Data Science, or a related technical discipline, or equivalent practical work experience.
  • 2+ years of experience building production-grade software using Python.
  • Strong software engineering fundamentals, including modular design, testing, debugging, and maintainable code.
  • Experience developing and integrating machine-learning or computer-vision models into real applications.
  • Experience with PyTorch or a comparable ML framework.
  • Experience building APIs and backend services; FastAPI or similar Python frameworks preferred.
  • Experience working with SQL databases and structured data.
  • Familiarity with modern AI techniques such as computer vision foundation models, embeddings, LLMs, or VLMs.
  • Proficiency with Git/source control, Linux development environments, and CI/CD workflows.
  • Ability to independently prototype, evaluate, and productionize new technical approaches.

Nice To Haves

  • Experience with TypeScript and React or similar modern web-development frameworks.
  • Experience building full-stack AI applications.
  • Experience with geospatial or 3D data, including one or more of: LiDAR and point cloudsPhotogrammetryGIS/geospatial imageryDigital twins or facility modelsCamera geometry and 3D reconstruction
  • Experience working with drone platforms, aerial imagery, mapping, or autonomous sensing systems.
  • Experience with ONNX, GPU inference, model optimization, or edge deployment.
  • Experience developing applications using LLMs or VLMs or SSL methods (SAM, DINO v3)
  • Experience with segmentation, feature matching, embedding models, or self-supervised computer vision.
  • Familiarity with Docker, cloud deployment, automated testing, and modern DevOps practices.
  • Familiarity with ROS/ROS 2, localization, sensor systems, or robotics software.
  • Experience working with drone, mobile, camera, or other real-world sensor datasets.

Responsibilities

  • Design and build AI-enabled applications from prototype through production.
  • Develop computer vision and multimodal AI workflows for imagery, video, drone data, geospatial data, and 3D environments.
  • Apply modern techniques including segmentation, feature extraction, self-supervised learning, foundation models, LLMs, and VLMs.
  • Develop AI workflows supporting drone-based inspection, mapping, perception, and emerging autonomous capabilities.
  • Develop scalable Python services and APIs using frameworks such as FastAPI.
  • Build data pipelines integrating AI inference, SQL databases, APIs, sensor-derived data, and external data sources.
  • Optimize and deploy AI models using PyTorch, ONNX, and related inference tooling.
  • Collaborate with engineers and domain experts to turn loosely defined technical problems into usable software.
  • Contribute to software architecture, testing, source control, automated deployment, and production reliability.
  • Rapidly evaluate emerging AI techniques and determine where they provide practical value.

Benefits

  • medical
  • dental
  • vision
  • paid time off
  • Employee Stock Ownership Plan (ESOP)
  • 401(k)
  • life insurance
  • flexible work schedules
  • holidays
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