MLOps Engineer

Booz Allen Hamilton•Bethesda, MD

About The Position

MLOps Engineer The Opportunity: As an experienced artificial intelligence and machine learning engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to conduct statistical analyses on business processes using ML techniques, including through the integration of large language models, makes you an integral part of delivering a customer-focused solution. We need your technical knowledge and desire to problem-solve to support new model development. As a machine learning engineer on our health team, you’ll train, test, deploy, and maintain models that learn from data. In this role, you’ll own and define the direction of mission-critical solutions by applying best-fit ML algorithms and technologies. You’ll be part of a large community of machine learning engineers across the company and collaborate with data scientists, software developers, and cloud data engineers to deliver world-class solutions to invent and generate models for automation and decision making. Your skills and extensive technical expertise will guide clients as they navigate the landscape of ML algorithms, tools, and frameworks. Join us. The world can’t wait.

Requirements

4+ years of experience with machine learning engineering on software engineering or data engineering projects, including for classification, regression, and decision-making
Experience building AI-enabled features or prototypes using LLMs, embeddings, or 3rd party APIs, including OpenAI or Anthropic
Experience with basic prompt engineering concepts and using LLM SDKs or frameworks, including LangChain or LlamaIndex
Experience using Databricks and MLFlow to efficiently manage data and ML workflows and optimizing performance and scalability for model experimentation, governance, or inferencing
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
Bachelor's degree in a Science, Technology, Engineering, or Mathematics (STEM) field

Nice To Haves

Experience building production-grade ML solutions, including work involving LLMs, agents, or complex automation frameworks
Experience with cloud platforms, including AWS, Azure, or GCP, and their AI or ML services
Experience developing back-end services and building or consuming RESTful APIs
Experience with Python or PySpark coding
Experience with container technology, including Docker or Kubernetes
Experience with software configuration management using Git
Knowledge of how to use Model Context Protocol to integrate agents into AI/ML-supported automation systems
Ability to work with limited guidance and clear direction
Possession of excellent verbal and written communication skills to communicate with peers and clients