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Machine Learning Engineer Active Secret Clearance - Striveworks
ML Engineer
Machine Learning Engineer building, deploying, and maintaining AI systems in a national‑security context, leveraging Python, AWS, Docker, and CI/CD pipelines to ensure reliable, scalable, and adaptable models for mission‑critical operations.
About the role
Key Responsibilities
- Design, develop, and production‑grade deploy machine learning models that support national security and business challenges.
- Implement robust CI/CD pipelines using Docker, Kubernetes, and AWS services to automate model training, testing, and deployment.
- Collaborate with data scientists, data engineers, and product teams to translate business requirements into scalable AI solutions.
- Monitor model performance in production, perform root‑cause analysis, and iterate for continuous improvement.
- Ensure compliance with security and privacy standards, maintaining active secret clearance throughout the project lifecycle.
Requirements
- Strong proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit‑learn.
- Hands‑on experience deploying models on AWS (SageMaker, ECS, Lambda) and managing containerized workloads with Docker.
- Solid understanding of CI/CD principles and tools (Git, Jenkins, GitHub Actions, ArgoCD).
- Excellent problem‑solving skills and ability to work in a fast‑paced, mission‑critical environment.
- Active secret clearance or ability to obtain one within 90 days.
Skills
pythonmachine learningawsdockercicd