Wealth.com Technology Internship Program: Applied Scientist (ai/ml)

Looking to gain practical, hands-on experience in the field of AI/ML? The Wealth.com Technology Internship Program helps passionate early career professionals gain real-world exposure to applying the latest advancements in Large Language Models (LLM), Computer Vision (CV) and Natural Language Processing (NLP) in the legal & financial tech sector. Applied Scientist Interns work collaboratively with Software Engineers and other Applied Scientists to pursue a broad range of AI initiatives. By using a combination of various state-of-the-art natural language and vision models, interns will help build complex legal AI assistants.

The Applied Scientist Intern will:

• Work with complex datasets from various sources to build Extract, Transform, and Load (ETL) data pipelines for downstream tasks
• Finetune and integrate the latest Large Language Models (LLMs) such as OpenAI/Gemini/MistralAI models into production systems.
• Train, finetune and deploy large-scale NLP and CV models to power complex document understanding experiences.
• Design and implement scalable and efficient Q&A RAG frameworks
• Collaborate with other product managers and engineers in the team to build tools to evaluate and improve the end-to-end AI quality of our production systems.
• Effectively communicating and demonstrating work to stakeholders

Basic Qualifications:

• Currently pursuing a Bachelor's, Master’s OR PhD degree in Computer Science, Electrical or Computer Engineering, or related field (e.g., statistics, predictive analytics, research)
• Experience building sophisticated RAG pipelines with LLMs
• OR Experience with common machine learning, deep learning frameworks like PyTorch/TensorFlow
• OR Experience developing and deploying complex AI/ML models to production

Preferred Qualifications:

• Currently pursuing a Master’s OR PhD degree in Computer Science, Electrical or Computer Engineering, or related field (e.g., statistics, predictive analytics, research) AND 1+ years related experience (e.g., statistics, predictive analytics, research)
• 1+ year(s) experience productionizing complex AI/ML models
• 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
• 1+ year(s) experience conducting research as part of a research program (in academic or industry settings).