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)

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
• Fullstack development experience (JS/TS/Node in particular)
• Demonstrated experience in similar roles in a startup or consultancy