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
