Collaborate with engineers, data scientists, and business analysts to understand requirements, refine models, and integrate LLMs into AI solutions
Incorporate RLHF and advanced techniques for tax-specific AI outputs.
Embed generative AI solutions into consolidation, reconciliation, and reporting processes.
Leverage LLMs to interpret unstructured tax documentation.
Development and implementation of Deep learning algorithms for AI solutions
Stay updated with recent trends in GENAI and apply the latest research and techniques to projects
Preprocess raw data, including text normalization, tokenization, and other techniques, to make it suitable for use with NLP models
Setup and train large language models and other state-of-the-art neural networks
Conduct thorough testing and validation to ensure accuracy and reliability of model implementations
Perform statistical analysis of results and optimize model performance for various computational environments, including cloud and edge computing platforms
Explore and propose innovative AI use cases to enhance tax functions
Partner with tax, finance, and IT teams to integrate AI workflows
Collaborate with legal teams to meet regulatory standards for tax data
Perform model audits to identify and mitigate risks
Monitor and optimize generative models for performance and scalability
What You Bring
6+ years of hands-on experience in data science
Solid understanding of object-oriented design patterns, concurrency/multithreading, and scalable AI and GenAI model deployment
Strong programming skills in Python, PyTorch, TensorFlow, and related libraries
Proficiency in RegEx, Spacy, NLTK, and NLP techniques for text representation and semantic extraction
Hands-on experience in developing, training, and fine-tuning LLMs and AI models
Practical understanding and experience in implementing techniques like CNN, RNN, GANs, RAG, Langchain, and Transformers
Expertise in Prompt Engineering techniques and various vector databases
Familiarity with Azure Cloud Computing Platform
Experience with Docker, Kubernetes, CI/CD pipelines
Experience with Deep learning, Computer Vision, CNN, RNN, LSTM
Experience with Vector Databases (Milvus, Postgres, etc.), Database Technologies