AI/ML Engineer (ML Ops) – Model Deployment & Optimization
Work Experience: 5+ Years of experience
Educational Qualifications: BS in Engineering, Computer Science, Information
Systems or equivalent
Security Clearance Requirements: Eligible to obtain Public Trust Clearance
Work Location:Hybrid or Remote for very strong candidates
Contract Duration: 6 months, extendable up to 1 year.
Skills & Experience Requirements
4+ years building, tuning, and deploying machine learning models in production environments.
Strong background in MLOps practices using MLflow or similar tools for model versioning, deployment, and governance.
Experience with microservices-based AI architectures and integration into operational platforms.
Proficiency in containerization (Docker, Kubernetes) and scalable inference serving.
Knowledge of explainability frameworks (e.g., SHAP, LIME) and bias detection techniques in AI systems.
Preferred Qualifications
Experience deploying AI models in regulated mission environments (healthcare, federal security, customs).
Familiarity with real-time risk scoring and decision-support integrations for government screening systems.
Hands-on use of graph transformers or hybrid rule+AI architectures.
Background in scaling AI solutions across multiple product categories or mission areas.
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