Qualifications 

• Ability to hold a position of public trust with the US government. 

• Bachelor's degree in computer science, data science/statistics, information systems, engineering, business, or a scientific or technical discipline 

• 2-4 years industry experience developing ML/AI solutions and a passion for solving complex problems.  

• Must have hands-on experience in building and deploying generative models, with a portfolio of relevant projects 

• Must be proficient in Python, with strong coding practices for scalability and reproducibility. 

• Demonstrated experience in building, training, and deploying generative models like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), or autoregressive models like Transformer-based architectures. 

• Demonstrated experience manipulating structured and unstructured data for analysis 

• Demonstrated experience using AI frameworks like TensorFlow, PyTorch, Keras, or JAX. 

• Ability to implement and modify complex neural network architectures. 

• Skilled in using data manipulation and analysis libraries such as Pandas, NumPy, SciPy, and Scikit-learn. 

• Experience with model training, fine-tuning, and evaluation using frameworks like PyTorch or TensorFlow. 

• Deep knowledge of natural language processing techniques, including tokenization, embeddings, attention mechanisms, and prompt engineering. 

• Hands-on experience with large language models (e.g., GPT, LLaMA, Claude, Mistral) and associated libraries (e.g., Hugging Face Transformers). 

• Familiar with retrieval-augmented generation (RAG), data labeling, synthetic data generation, and data governance best practices. 

• Proficiency in Python and ML tooling (e.g., Jupyter, Git, Docker, APIs). Able to work in cross-functional teams to deliver AI capabilities into production environments, and write modular/reusable code. 

• Experience in Cloud analytics (AWS, Azure, or Google Cloud Platform - GCP) with tools such as AWS SageMaker, AWS Bedrock, Azure OpenAI, etc. 

• Experience with DevSecOps, as it applies to data science and MLOps 

• Data visualization skills in Tableau, Power BI, D3, ArcGIS, or similar are a plus 

• Experience with Elasticsearch, AWS Kendra, Azure Cognitive Search, or similar tool is a plus