Jobs at Expedition Technology, Inc.

Develop and optimize ML and computer vision models for hyperspectral and multi-modal sensor data, build detection/tracking and data fusion algorithms, translate research into deployable software, and support solutions across cloud and low SWaP environments for geospatial intelligence applications.

Design and implement backend and systems-level software for defense and intelligence, integrating signal-processing and machine-learning algorithms into real-time, field-ready systems. Collaborate in small teams to prototype, architect, and deploy extensible solutions that integrate with existing infrastructure while translating customer requirements into development priorities.

Build and maintain backend services for the Training Data Storefront (TDS): design and implement features, RESTful APIs and streaming services, optimize performance, use Python, Docker, Kubernetes and AWS, follow SDLC best practices, mentor teammates, and work directly with end users in an Agile environment.

Design, develop, and deploy cloud-native AWS applications in cleared environments. Manage C2S and GovCloud deployments, create reusable CloudFormation templates, implement logic with Lambda or ECS Fargate, maintain containerized CI/CD pipelines, and support DevOps practices across high-side and low-side environments.

Design, prototype, and operationalize ML models and data pipelines for temporal, geospatial, and track-based mission data. Build data processing, feature engineering, containerized cloud deployments (AWS/Docker/Kubernetes), APIs, and scalable evaluation/monitoring workflows while following Agile and software engineering best practices.

Design, develop, and maintain full-stack web applications and scalable backend services for a DoD/IC Training Data Storefront. Implement responsive frontends, Python-based APIs, containerized deployments on AWS, and ensure performance, security, and test coverage while collaborating in an Agile team.

Develop and deploy containerized Python applications and models to Kubernetes; build CI/CD pipelines, infrastructure-as-code (CloudFormation/Terraform/Packer); troubleshoot Linux networking and services; implement DevSecOps capabilities compliant with NIST/CMMC; support developers and model builders with tooling and release engineering.

Design, implement, and maintain production-grade Python services and internal tools; lead technical design for scalable, available cloud/containerized systems; mentor junior engineers; support DevSecOps, testing, security, observability; adopt AI-assisted workflows and contribute to AI/ML or data-driven systems when applicable.

Design and implement advanced digital signal processing and machine learning algorithms for radar, EW, SIGINT, and RF geolocation; prototype and transition DSP/ML models to real-time, field-ready software across on‑premises and cloud environments in support of US intelligence and defense missions.

Design and deliver secure cloud-native CI/CD pipelines and DevSecOps capabilities for DoD/Intelligence programs: write/review Python, build containers and orchestration, implement IaC, automate cloud processes, troubleshoot Linux networking, and ensure compliance with NIST/CMMC/CIS.

Develop and deploy deep learning computer-vision systems: source and curate data, design and train models (object detection), implement production-ready PyTorch/Python software, integrate with AWS, apply CI/CD and testing, and collaborate on research and technical solutions for intelligence-focused applications.

Design, develop, and deploy cloud-native applications on AWS for cleared environments. Manage cleared cloud deployments (C2S/GovCloud), build reusable CloudFormation templates, support DevOps/CI-CD pipelines, and containerized applications.

Develop responsive, user-facing web application components for a centralized AI/ML annotation and model repository. Translate UI/UX designs to interfaces, integrate with backend services via REST/GraphQL, implement performance and security best practices, and author frontend tests and automation. Participate in Agile development and collaborate with end users and designers while maintaining operational systems.

Build and maintain Python-based services and internal tools to support verification, validation, testing, and evaluation workflows for DoD and Intel missions. Design scalable, testable software systems, collaborate on architecture and observability, support containerized deployments and CI/CD automation, and mentor engineering teammates in mission-critical environments.

Design and implement software solutions for US defense and intelligence, integrating signal-processing and machine-learning models into real-time, field-ready systems. Collaborate in small teams, prototype algorithms rapidly, and build extensible architectures that translate customer requirements into deployable software.

Develop backend systems and ML pipelines for computer-vision applications using Python, Docker, Kubernetes and AWS. Build RESTful APIs and streaming services, optimize performance, follow SDLC best practices, and collaborate in an Agile team to deploy containerized deep learning models.