Sr. AI/ML Engineer II (6707)
$212,000–$248,000 year
On-siteReston, Virginia, United States
Job Summary
Analyze complex datasets to assess performance or identify new patterns, then build, train, operationalize, and maintain AI/ML models in production. Apply machine learning techniques to immigration-related data sets and present results to diverse audiences. Support architectural leadership and technical advisement to ensure identity management system technologies meet security requirements while engaging with senior executives at a public-facing Federal agency. Design, develop, and deploy containerized AI/ML solutions into classified AWS cloud environments at IL6+, utilizing open-source models where possible. Automate and optimize manual processes through data analytics and algorithm implementation within a DevSecOps CI/CD pipeline.
Required Qualifications
- Minimum 10 years experience
- Bachelor's degree or equivalent experience
- Active TS/SCI CI Clearance
- You have extensive experience using open-source models to the largest extent possible or provide a comparable analysis and justification for using proprietary models
- Expert experience with at least two of following AI/ML methods: Generative AI/LLMs, NLP, RAG, and neural networks
- At least 8 years experience with at least two following technologies: Python, R, Anaconda, Numpy, TensorFlow, Keras, SciKit-Learn, and Postgres
- You have at least 8 years experience designing, implementing, and maintaining data architecture and services to be used for AI/ML
- able to maintain the AI/ML models through user stories and DevSecOps CI/CD pipeline including any optimization and evaluation of alternatives
- Expert experience designing, developing, and deploying AI/ML solutions into classified AWS cloud environments at IL6+
- You have the ability to perform data analytics on program related or system related activities
- This will include assessing performance and manual processes implementing methods/algorithms to automate and optimize
- Strong experience with designing, developing, and deploying containerized AI/ML solutions
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