AL/ML Engineer, Lead

Booz Allen Hamilton•Atlanta, GA

1d•$128,700 - $292,000•Onsite

About The Position

As an experienced engineer, you know that machine learning (ML) is critical to understanding and processing massive datasets. Your ability to conduct statistical analyses on business processes using ML techniques makes you an integral part of delivering a customer-focused solution. We need your technical knowledge and desire to problem-solve to support public health and safety. As an ML engineer on our 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 ML engineers across the company and collaborate with data engineers, data scientists, solutions architects, enterprise architects, and product owners to deliver world-class solutions. You’ll help design and develop enterprise ML operations frameworks, support mentorship and training initiatives, process data and information at a massive scale, and perform A/B testing tasks on statistical models, ML algorithms, and systems. Your advanced skills and technical expertise will guide clients as they navigate the evolving landscape of ML, Generative AI, AI agents, and retrieval-augmented generation (RAG) technologies.

Requirements

5+ years of experience designing, developing, and deploying ML models and AI solutions using Python
5+ years of experience with Generative AI, LLMs, AI agents, or RAG applications in enterprise environments
Experience developing AI evaluation strategies and working with MCP-enabled systems
Experience with ML frameworks and libraries such as TensorFlow or PyTorch
Experience with data engineering using PySpark, SQL, and Palantir Foundry, including Foundry AIP
Experience with Prompt Buddy, Codex, Claude, or OpenEvidence in enterprise environments
Experience deploying ML solutions at scale using MLOps tools such as MLflow, and cloud platforms such as Azure, Databricks, or Domino
Ability to implement AI agent architectures, retrieval optimization, and memory or state management workflows
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
Bachelor's degree in CS, Engineering, or Data Science

Nice To Haves

Experience with open-source LLMs such as LLaMA, Gemma, or Phi
Experience in deep learning, NLP, conversational AI, or computer vision
Experience supporting healthcare, biomedical, or public health AI/ML initiatives and government public health data systems
Experience with chatbot development or end-to-end AI application deployment
Experience with containerization, orchestration, CI/CD, and full-stack ML application deployment
Experience working in Agile environments using tools such as Jira
Experience writing technical documentation and presenting technical solutions to broad audiences
Ability to collaborate effectively in matrixed environments with cross-functional stakeholders
Master’s degree

Responsibilities

Build and maintain complex data pipelines using PySpark and Palantir Foundry to support AI and analytical workloads.
Design and implement ML workflows, including Generative AI, AI agents, MCP-enabled systems, and RAG pipelines for public health use cases.
Develop robust AI evaluation strategies to ensure the quality, reliability, and performance of deployed AI solutions.
Design AI architectures supporting agent memory, state management, retrieval optimization, and interaction with structured and unstructured public health data.
Collaborate with cross-functional teams to translate mission requirements into scalable AI/ML solutions while maintaining technical documentation and governance standards.
Define and enforce data quality, privacy, anonymization, auditing, and ethical AI standards in compliance with public health and government requirements.