Automate tax form population, classify documents, predict client outcomes, and power intelligent tools in the tax automation ecosystem.
Requirements
- Basic proficiency in Python and familiarity with libraries like scikit-learn, PyTorch, or TensorFlow.
- Exposure to APIs (e.g., OpenAI, Azure AI) or NLP/OCR tools (e.g., LangChain, Tesseract) is a plus.
- Interest in working with structured/unstructured data, especially financial or tax documents.
- Familiarity with Docker, Airflow, or MLflow.
- Interest in regulatory or IRS compliance for AI models.
- Exposure to Azure Synapse, Power BI, or Snowflake.
Responsibilities
- Assist in designing, building, and fine-tuning machine learning models for document classification, entity extraction, and outcome prediction using tools like scikit-learn, PyTorch, or TensorFlow.
- Support data pipelines by Collaborating with Data Engineers to create ETL pipelines, feature stores, and data validation workflows, working with tax and CRM teams to define training data.
- Help establish metrics like recall, precision, and accuracy to assess model performance, optimizing to reduce errors in tax form extraction and chatbot responses.
- Support model deployment using tools like MLflow, FastAPI, or Streamlit, and assist in versioning, logging, and monitoring live systems.
- Contribute to a dynamic team, gaining hands-on experience with real-world AI applications in tax automation.
Other
- Recent graduate (0–2 years of experience, including internships) in AI, NLP, computer science, or related fields.
- Exceptional communication skills to bridge technical and non-technical teams.
- Eager to learn, with a proactive approach to problem-solving.
- Strong documentation habits and a team-oriented mindset.
- Irvine, CA - onsite preferred
