Generative AI Data Scientist

Formulating, design and deliver AI/Client-based decision-making frameworks and models for business outcomes. Measure and justify AI/Client based solution values.Python GenAI Engineer with expertise in developing, fine-tuning, and integrating AI models, particularly in natural language processing (NLP). This role focuses on building generative AI solutions for summarization tasks and other NLP applications.

Experience in AI/Client development with a strong focus on NLP and generative models, using frameworks such as TensorFlow, PyTorch, and Hugging Face

Expertise in Python, with experience in libraries like Transformers, NLTK, SpaCy, Gensim, and data manipulation tools such as Pandas and NumPy

Expertise in frameworks such as TensorFlow, PyTorch, and Hugging Face

Strong proficiency in Python, with experience in libraries like Transformers and NLTK

Familiarity with generative AI models such as OpenAI's GPT, Llama, and supporting libraries like VLLM

Experience with cloud platforms (AWS, Azure), containerization (Docker), and using CI/CD pipelines for machine learning model deployment

Knowledge of SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Elasticsearch) databases, and how to structure data pipelines for efficient data processing. Experience optimizing databases (SQL: PostgreSQL, MySQL; NoSQL: MongoDB, Elasticsearch) to support efficient data storage and retrieval for AI models.

Experience in healthcare, particularly working with unstructured medical records in clinical settings, leveraging NLP models for insight extraction.

Experience working with human-in-the-loop systems, incorporating clinician/end-user feedback and leveraging tools like SciPy and NumPy to improve AI model accuracy

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.