As a Machine Learning Engineer on our team you will build and iteratively refine model pipelines that enable rich text experiences on Wallet products. You will conduct experiments and create prototypes for new approaches to improve the quality of our generative language models translating customer needs into analytical solution. You will work hand in hand with software engineers data scientists and product partners. Finally you will implement the building blocks and infrastructure that bring these innovations into our production pipelines and contribute evaluate metrics for measuring forward RESPONSIBILITIES- Development and maintenance of modeling pipelines that are deployed to production and reach global scale- Definition of robust automated evaluation metrics to enable continuous model improvements- Failure analysis to understand shortcomings and model sensitivities- Curation and synthesis of representative training and evaluation data- Implementation of experiments and simulations to assess proposed model changes
MS or PhD in Computer Science or related field with at least 2 years of industry experience
Strong Python programming skills with experience developing production-quality Python modules
Solid background in machine learning data science natural language processing or statistics
Experience building and maintaining model pipelines end-to-end from data curation to evaluation
Ability to design and implement experiments that bring NLP research ideas into production
Familiarity with LLMs RHLF prompt engineering data synthesis automatic evaluation and RAG
Excellent written and verbal communication skills.
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