Machine Learning Operations Engineer

$75,600 - $172,000/Yr

Booz Allen Hamilton - Washington, DC

Part-time,Full-time - Mid Level

Washington, DC

Professional, Scientific, and Technical Services

About the position

The Machine Learning Operations Engineer role focuses on architecting, developing, and implementing systems that enhance software development efficiency within the Department of Defense. This position is designed for individuals with a blend of data science, engineering, and communication skills, aiming to streamline the software development lifecycle through automation and cloud resources. The engineer will work on impactful projects, utilizing open-source tools and continuous integration/delivery practices to support agile teams in delivering innovative solutions.

Responsibilities

• Streamline the software development lifecycle from requirements to production monitoring.
• Incorporate open-source tools and automation to reduce tedious tasks for developers.
• Implement continuous integration and delivery to minimize manual testing and troubleshooting.
• Develop and deploy machine learning models and production-grade solutions using Docker or Kubernetes.
• Collaborate with teams to enhance software development processes and tools.

Requirements

• 2+ years of experience in machine learning, data science, software engineering, data analytics, or DevOps.
• Experience building and deploying machine learning models.
• Proficiency in programming languages for data science, including Python or Java.
• Experience with Docker or Kubernetes for production-grade solutions.
• Secret clearance and a Bachelor's degree.

Nice-to-haves

• Experience architecting and deploying AI solutions with generative models, including large language models (LLMs).
• Familiarity with CI/CD pipelines, including Jenkins or Git Actions.
• Experience with cloud platforms such as AWS, Google Cloud, or Azure, and associated data platforms like Databricks or AWS SageMaker.
• Knowledge of CI/CD tooling, including Gitlab and Tekton.
• Experience with model serving solutions like KServe and Seldon Core.
• Familiarity with automation technologies, including Ansible and Terraform.

Benefits

• Health insurance
• Life insurance
• Disability insurance
• Financial benefits
• Retirement benefits
• Paid leave
• Professional development
• Tuition assistance
• Work-life programs
• Dependent care support