Data Engineer

Job Description:

Must be strong with Python for ML pipelines specifically with Py torch and scikit-learn

AWS is required, building pipelines within

Should have a background in LLM  (langchain, agents, extensive prompt engineering)

The "strong additional requirements" below are required.

Responsibilities:

Ingesting, structuring and analyzing a wide range of unstructured datasources

Designing, maintaining and orchestrating data pipelines in an AWS environment for production processing and training flows

Continuously evaluate, analyze, test and improve the quality, privacy and performance of our data systems

Contribute across the product, where  - from front-end UX and product design, API/systems architecture and ML processing/training

Minimum Qualifications:

• 3+ years of experience ingesting, analyzing and structuring a wide variety of datasources
• Significant experience building and maintaining data pipelines in a production environment
• Strong database/SQL, python, pandas (or equivalent) experience 

Prior experience working in fast paced environments and tackling problems across the stack with quick iterations while maintaining a high quality bar. 

Strong Additional Qualifications:

Significant healthcare data experience

LLM experience (langchain, agents, extensive prompt engineering)

MLE  Experience - pytorch, scikit-learn, etc..

Extensive production AWS, container and/or data orchestration experience

Full stack development experience (JS/TS/Node in particular)