Machine Learning Operations Engineer
@ SAIC

Fort Belvoir, Virginia, United States
$120,000
On Site
Full Time
Posted 23 days ago

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Job Details

About the Machine Learning Operations Engineer Role

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 machine learning models within the Army Intelligence & Security Enterprise (AISE).

Key Responsibilities

  • Design and implement MLOps pipelines for automated deployment and monitoring.
  • Develop CI/CD tools and frameworks for AI/ML systems.
  • Collaborate with data scientists, ML engineers, and cloud engineers to optimize model performance.
  • Monitor and manage deployed models, addressing performance drift and scheduling retraining.
  • Ensure compliance with security protocols and governance policies.
  • Stay updated on MLOps practices, tools, and industry advancements.
  • Integrate AI/ML solutions to support mission-critical intelligence capabilities.

Required Education & Qualifications

Bachelor's degree plus 5+ years of experience; Master's with 3+ years of experience; or PhD/JD with relevant experience. Alternatively, 4 years of relevant work experience may be considered. Proficiency in Python or Bash, expertise in MLOps tools (e.g., MLflow, Kubeflow), containerization (Docker, Kubernetes), cloud platforms (AWS, Azure, Google Cloud), and experience with LLMs is required.

Desired Qualifications

Advanced degree in Machine Learning, AI, or related field, experience with monitoring tools (Prometheus, Grafana), and familiarity with Army Intelligence Enterprise data workflows and version control practices.

Security Clearance

Candidates must have an active TS/SCI clearance with the ability to obtain Polygraph.

Key skills/competency

  • MLOps
  • Machine Learning
  • DevOps
  • CI/CD
  • Python
  • Containerization
  • Cloud Platforms
  • Monitoring
  • Security
  • Collaboration
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How to Get Hired at SAIC

🎯 Tips for Getting Hired

  • Customize your resume: Tailor your experience for MLOps and DevOps roles.
  • Highlight technical skills: Showcase Python, Docker, Kubernetes proficiency.
  • Research SAIC culture: Understand their projects and security standards.
  • Prepare for interviews: Practice discussing pipeline automation and cloud platforms.

📝 Interview Preparation Advice

Technical Preparation

Review ML pipeline automation frameworks.
Practice Python scripting and Bash commands.
Familiarize with Docker and Kubernetes deployments.
Study cloud platform integration and CI/CD tools.

Behavioral Questions

Describe a time you solved complex issues.
Explain your approach to cross-team collaboration.
Discuss maintaining system reliability under pressure.
Share experiences adapting to evolving technologies.

Frequently Asked Questions