Booz Allen needs a Machine Learning Engineer to train, test, deploy, and maintain models that learn from data to support federal healthcare. The role involves conducting statistical analyses using machine learning techniques and defining the direction of mission-critical solutions by applying best-fit ML algorithms and technologies.
Requirements
- Experience with machine learning engineering, or postdoctoral research for machine learning
- Experience with natural language processing and language models
- Experience with RAG and Generative AI techniques
- Experience with programming in Python, Java, or C++
- Experience with developing software architectures with containerization tools, including Docker and Kubernetes
- Experience with machine learning, including linear, reinforcement learning, tree based, or deep learning-based methods and regularization approaches
- Experience with databases, including SQL
Responsibilities
- train, test, deploy, and maintain models that learn from data
- conduct statistical analyses on business processes using machine learning (ML) techniques
- own and define the direction of mission-critical solutions by applying best-fit ML algorithms and technologies
- collaborate with data engineers, data scientists, solutions architects, and product owners to deliver world class solutions
- deliver mentorship, training, and solutions to real world problems
- process data and information at a massive scale
- perform A/B testing tasks on statistical models, ML algorithms, and systems
Other
- Secret clearance is required
- Bachelor's degree
- Ability to work in a Linux environment with Bash Scripting
- Master's degree
- Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information
