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Machine Learning Operations Engineer
SAIC
Original Job Summary
Overview
SAIC is seeking a Machine Learning Operations Engineer to join our team in Fort Belvoir, Virginia. In this role, you will streamline the deployment, monitoring, and maintenance of ML models and systems within the Army Intelligence & Security Enterprise (AISE).
Job Duties
- Design and implement MLOps pipelines for ML model deployment.
- Develop CI/CD tools for AI/ML systems.
- Troubleshoot operational issues in deployed models.
- Collaborate with data scientists and ML engineers.
- Monitor performance, drift, and reliability of models.
- Implement retraining workflows as needed.
- Ensure compliance with security protocols and governance policies.
- Stay updated on advancements in MLOps practices and tools.
- Support operational integration of AI/ML solutions for enhanced intelligence.
Required Education & Qualifications
Bachelor's with five or more years of experience; Master's with three or more years of experience; PhD or JD with no experience requirements; or four years of experience in lieu of a degree.
Required skills include proficiency in Python or Bash, strong understanding of MLOps tools (MLflow, Kubeflow, TensorFlow Extended), containerization (Docker), orchestration (Kubernetes), and cloud-based AI/ML platforms (AWS, Azure, Google Cloud). Experience with large language models (e.g., GPT) is also important.
Clearance
Candidates must have an active TS/SCI with the ability to obtain a TS/SCI with Polygraph.
Key skills/competency
- MLOps
- CI/CD
- Python
- Containerization
- Kubernetes
- Cloud Platforms
- Monitoring
- DevOps
- Troubleshooting
- Security Compliance
How to Get Hired at SAIC
🎯 Tips for Getting Hired
- Research SAIC's culture: Study their mission, values, and employee testimonials.
- Customize your resume: Highlight MLOps and CI/CD experience.
- Prepare technical examples: Showcase projects with Python and Kubernetes.
- Practice interview insights: Emphasize collaboration and troubleshooting skills.