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# Junior Machine Learning Engineer

- **Company:** Tax Relief Advocates
- **Location:** Irvine, CA, United States
- **Experience:** Starter
- **Salary:** $85,000.0 - $100,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Google Docs, Python (Programming Language), Machine Learning, Natural Language Processing, Named Entity Recognition, Role-Based Access Control, Power BI, Tensorflow, Unstructured Data, Management of Software Versions, Data Logging, Pytorch, Large Language Models, Snowflake, AWS Lambda, Fastapi, Containerization, Scikit Learn, Information Technology, Machine Learning Operations, Streamlit Framework, Document Classification, Azure Synapse Analytics, Serverless Computing, Docker
- **Published:** July 29, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=e1d5cd7586eaab60

## About the Role

Are you a recent grad or early-career tech enthusiast ready to dive into AI and machine learning? Join our innovative team in Irvine, CA, to build cutting-edge models that automate tax form population, classify documents, predict client outcomes, and power intelligent tools in our tax automation ecosystem. No extensive experience required - just a passion for learning, stellar communication skills, and big ideas for transforming tax processes!, * Education & Experience: Recent graduate (0-2 years of experience, including internships) in AI, NLP, computer science, or related fields.

 * Technical Skills:
*

 + Basic proficiency in Python and familiarity with libraries like scikit-learn, PyTorch, or TensorFlow; familiarity with pandas for document extraction, a PDF extraction library, and/or token estimation libraries is a plus.
 + Experience working with LLM APIs and their payload outputs (e.g., OpenAI, Azure AI), along with OCR/document intelligence tools (e.g., Azure Document Intelligence, Google Document AI). Interest in working with structured/unstructured data, especially financial or tax documents., + 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., + Solid understanding of containerization, with experience building custom Docker images.
 + Familiarity with security fundamentals like role-based access control or JWT-based authentication.
 + Interest in regulatory or IRS compliance for AI models.
 + Exposure to Azure Synapse, Power BI, or Snowflake.
 + Experience with serverless architectures (e.g., AWS Lambda, Azure Functions) is a plus.

## Description

* 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 internal departments by transforming legacy workflows through the integration of AI-powered tools.
 * Evaluate Performance: Help establish metrics like recall, precision, and accuracy to assess model performance, optimizing to reduce errors in tax form extraction and chatbot responses.
 * Deploy & Monitor: Support model deployment using tools like MLflow, FastAPI, or Streamlit, and assist in versioning, logging, and monitoring live systems.
 * Learn & Grow: Contribute to a dynamic team, gaining hands-on experience with real-world AI applications in tax automation.


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