Machine Learning Engineer
📍
New York, United States
🧪
Entry level
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)
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)