Job description

Must be on-site five days a week in Woodlawn, MD Strong knowledge of AI/ML/LLM, RAG, SQL, Python, NLP, AWS, Generative AI. • Hands on experience in Python, RAG, NLP, ML and Generative AI • Well versed in SQL and analyzing trends and transactional data. • Understand real world challenges and develop automated data solutions • Develop, test, and deploy new techniques for NLP understanding • Scalable development/deployment of ML and Generative AI approaches (such as Large Language Models (LLMs) • Train and optimize NLP/LLM models and create Python based pipelines • Experience building cloud native solutions on AWS • Determine the nature of analytic problems, evaluate options, and offer recommendations for resolution. • Advise on the methods and data needed and/or available to evaluate the (intelligence or data) problem. • Collaborate with data collectors and analysts to identify and close gaps on complex monitoring problems. • Provide accurate, timely, complex, and sophisticated data analysis. • Bachelor's degree in Statistics, Applied Mathematics, Computer Science, or Information Science with industry experience on RAG LLM, Python, NLP, data science, AI/ML/LLM engineering. • Overall 10+ years' experience in IT industry • Must be able to obtain and maintain a Public Trust. Contract requirement. These Skills Will Help You Succeed In This Position • Experience with Natural Language Processing (NLP), Generative AI and Large Language Models (LLM) • Fluency in Python Programming, version control and collaboration with GIT, standard Python packages (ex. Pandas, numpy, matplotlib) and ML frameworks • Knowledge of TensorFlow, PyTorch, Pandas, scikit-learn, NLTK, Azure ML (optional), Amazon Web Services EC2. • Experience with scalable data engineering frameworks such as Apache Spark and orchestration frameworks such as Airflow, and/or experience with semantic search. • Expert knowledge in conducting data analysis and applying advanced statistical concepts and ML methods to build, train, test, and evaluate a variety of supervised and unsupervised analytic models. • Experience with ML model deployment and operations like DevOps, MLOps, LLMOps. • Experience with NLP and Generative AI libraries like regular expressions (e.g., spacy, langchain), text annotation tools and semantic frameworks. • Ability to clean and process large amounts of real-world data. • Experience retrieving and manipulating data from a variety of data sources included DB2, Oracle, SQL Server, Hadoop and flat files. • Experience with database management systems (e.g., PostgresSQL, MySQL, SQLite, SQL, etc.) • Excellent analytical skills to identify potential risks and propose effective solutions.

Requirements