Data Engineer

Must be strong with Python for ML pipelines specifically with Pytorch and scikit-learn AWS is required, building pipelines within, Should have a background in LLM (langchain, agents, extensive prompt engineering)

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

Fullstack development experience (JS/TS/Node in particular)

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