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Freedom Technology Solutions Group

Machine Learning Engineer 727

St. Louis, MOmidAdded today

About this role

Freedom Technology Solutions Group is hiring a Machine Learning Engineer to design, deploy, and optimize production AI/ML systems for government geospatial and intelligence applications. You'll bridge research and production, working with cloud infrastructure, containerization, and MLOps practices in secure environments.

What you'll do

  • Design, train, validate, and deploy machine learning models into production
  • Build and optimize production inference pipelines and feature engineering workflows
  • Implement MLOps infrastructure supporting CI/CD and model monitoring
  • Develop scalable APIs exposing AI capabilities and deploy workloads to AWS
  • Support computer vision, NLP, and geospatial AI initiatives
  • Collaborate with stakeholders to gather requirements, document processes, and ensure mission alignment

What they're looking for

  • Python, PyTorch, TensorFlow, Scikit-learn
  • MLOps and model deployment (MLflow, SageMaker)
  • AWS cloud services (ECS, EKS, Lambda, Kubernetes)
  • Docker/Podman containerization and GitLab CI/CD
  • Geospatial tools (GDAL, Rasterio, PostGIS, QGIS)
  • Database design (PostgreSQL, Aurora, Oracle Spatial)
  • Linux system administration
  • Stakeholder communication and requirements gathering

Benefits

  • Matching 401(k) and fully paid medical insurance
  • Generous paid time off with company closure days
  • Paid training and tuition reimbursement
  • Fully paid life and disability coverage
  • Referral bonuses and annual logo wear allowance
  • Company-sponsored events and flexible work environment
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Freedom Technology Solutions Group

Freedom Technology Solutions Group builds intelligence analysis products and enterprise digital transformation solutions, with a focus on secure, mission-critical infrastructure and AI/ML capabilities. The company is hiring technical leaders and engineers including test engineers, full-stack developers, system architects, and DevOps specialists to support modernization, cloud infrastructure (AWS/Azure), and secure environments.

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Likely interview questions

  • Describe your experience moving machine learning models from research to production—what were the key challenges?
  • How have you implemented MLOps pipelines, and which tools did you use for model tracking and deployment?
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