Machine Learning Engineer 727

Responsibilities

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• Design, train, validate, and deploy machine learning models
• Build production inference pipelines
• Develop feature engineering workflows
• Optimize model performance and resource utilization
• Implement MLOps pipelines supporting continuous integration and deployment
• Build scalable APIs exposing AI capabilities
• Monitor model drift and operational performance
• Collaborate with Data Scientists and Software Engineers
• Deploy AI workloads into AWS cloud environments
• Support computer vision, NLP, and geospatial AI initiatives
• Collaborate with architects, data scientists, and mission stakeholders to gather, document, and refine customer requirements, including data mapping and integration needs
• Assist in implementing integration solutions in collaboration with development team members
• Facilitate communication between stakeholders to ensure timely and effective requirements execution
• Ensure activities align with established processes, standards, and mission objectives
• Contribute to documentation of processes, procedures, integration patterns, and lessons learned

Key Technologies

• A
• Python
• PyTorch
• TensorFlow
• Scikit-learn
• Hugging Face
• MLflow
• Docker/Podman
• Kubernetes/EKS
• ECS
• Lambda
• SageMaker
• GitLab CI/CD
• Linux
• PostgreSQL/PostGIS, Aurora, Oracle (w/Spatial)
• Redis, Elasticache
• GDAL, Rasterio, OGR

Required Qualifications

• Active TS/SCI clearance (eligible for CI Poly)
• 1-3(Junior), 3-7(Journeyman), 8-11 (Senior), >12 (Principal) years of experience in software development, system integration, or technical support roles
• Experience working directly with customers or stakeholders in a technical or mission environment
• Strong communication and coordination skills across technical and non-technical teams
• Experience gathering and documenting requirements
• Ability to manage multiple tasks and priorities in a dynamic environment
• Familiarity with Agile development practices
• Experience using GitLab or similar tools for collaboration and tracking

Desired Qualifications

• Experience deploying production AI systems
• Experience with computer vision
• Experience with large language models
• Geospatial AI experience
• AWS AI services
• Experience processing satellite imagery
• Familiarity secure data movement environments
• Experience working with enterprise service processes such as Service+
• Development or scripting experience (Python, JavaScript, or similar)
• Geospatial/GIS development a plus
• Experience with data mapping or integration workflows (using JSON or other object notation)
• Familiarity with operational dashboards and metrics reporting
• Experience supporting customer requirement implementation and/or system integration efforts

What's in It for You?

• Flexible work environment
• A team mentality - work with friendly, like-minded professionals
• Work with innovative, cutting edge technologies

Enjoy extremely competitive compensation and benefits

• A work-life balance you can count on
• Opportunities to grow and advance your career on our dime

The Benefits You Get with Freedom

• Amazing benefits including matching 401k, fully paid medical, and more
• Generous paid time off - including paid site closure days
• Competitive salary offerings
• Paid training and tuition reimbursement
• Referral bonuses
• Fully paid life and disability
• Annual logo wear allowance

Company sponsored events (game nights, holiday party, summer party, happy hours)

• Interested in learning more about Freedom and our culture?
• Contact us today!
• We're constantly hosting hiring events in our office and elsewhere, to help you get a sense of what life is like at Freedom before joining the team.