One of our clients is seeking an AI/ML Engineer to join their Engineering team responsible for the development, maintenance, and reliability of cloud-based applications on DoD platform environments.
Position: AI/ML Engineer
Location: Hybrid
Position Type: Full Time
Clearance: Public Trust/US Citizen
Job responsibilities
- Design, develop, train, test, deploy, and maintain AI and machine learning models for enterprise-scale and Government applications.
- Develop and operationalize production of AI/ML solutions, ensuring models and supporting systems are reliable, scalable, maintainable, and appropriate for VA mission requirements.
- Collect, clean, transform, analyze, and prepare structured and unstructured data for AI/ML model development, training, testing, and evaluation.
- Evaluate potential AI technologies, models, tools, frameworks, and architectures and recommend solutions appropriate for complex Federal Government and cybersecurity use cases.
- Apply AI and machine learning techniques to solve real-world business, cybersecurity, engineering, analytics, and operational problems across a large enterprise environment.
- Develop and support Generative AI and Large Language Model (LLM) solutions, including model configuration, system prompts, classifiers, fine-tuning, content moderation, safety filters, and other model controls.
- Evaluate AI-generated outputs for accuracy, factuality, grounding, reliability, bias, helpfulness, honesty, and overall model performance before outputs are incorporated into VA efforts.
- Design and execute AI/ML model evaluation and validation methodologies, including benchmark testing and comparative evaluation of model outputs.
Minimum qualifications
- Minimum of 5 years of experience in relevant fields including IT security, data science, software engineering, design, development, or deployment of AI or machine learning systems in enterprise or Government environments
- Experience working on data science, machine learning, or AI projects, either through internships, research projects, or professional roles.
- Experience building, training, and deploying machine learning models and AI systems in a production environment.
- Experience collaborating with cross-functional teams, including data scientists, software developers, and domain experts.
- Experience in data collection, cleaning, and analysis techniques to prepare datasets for AI modeling.
- Experience applying AI solutions to real-world problems in various enterprises and domains such as large corporations and Government agencies similar in size/scope to GSA, IRS, DoD or VA
Preferred qualifications
- Master’s or PhD in AI, Computer Science, or related technical field.
- Experience implementing multi-agent systems using frameworks like ReAct and self-reflection.
- Experience debugging Agent logic and optimizing tool selection, including tracing conversation IDs across microservices to identify and resolve failures in real-time.
- Experience connecting agents to enterprise knowledge bases and optimizing RAG chunking to prevent hallucinations.
- Track record of troubleshooting live, high-traffic systems during critical windows.
Flexible work from home options available.