Our organization manages a diverse array of programs each presenting a unique set of challenges however all programs fundamentally focus on evaluating machine learning algorithms and assessing their this role you will work closely with cross-functional teams leveraging the expertise of domain specialists and project owners while adapting our methodologies as we gain new insights. We aim to support teams in identifying gaps assessing risks and driving towards impactful this role you will:- Evaluate Machine Learning Models: Analyze and validate machine learning and computer vision models to ensure they meet performance standards.- Develop Metrics: Design and implement metrics to measure the effectiveness and accuracy of models.- Failure Analysis: Perform detailed failure analysis to understand model weaknesses and identify areas for improvement.- Data Processing: Preprocess and clean large datasets to prepare them for modeling.- Model Optimization: Optimize models for performance and scalability applying state-of-the-art techniques.- Collaborate: Work closely with cross-functional teams including software engineers product managers and other data scientists to integrate models into production.
BS or MS and in Data scientist or Computer Vision or related filed
Solid background in data science LLM machine learning Computer vision and statistical data analysis
Advanced programming skills in data manipulation & processing (SQL & Python preferred)
Demonstrated experience in in-depth analysis of machine learning model failures
Demonstrated experience using LLM-as-Judge prompt pipeline for Failure analysis
Experience crafting conducting analyzing and interpreting experiments and investigations
Expertise in data wrangling and developing data visualizations & reporting with toolings such as Tableau Superset AWS etc.
Experience managing complex programs in the industry
Familiar with machine learning interpretability method
Familiar with various foundation models such as CGPT4V LLAMA CLIP
Detail-oriented to keep track of and understand the workings of complex algorithms
Self-motivated curious creative and critical thinking capabilities to improve data quality evaluation methods for diverse and complex data annotation programs
Outstanding verbal and written communication skills along with strong collaborative abilities
Outstanding communications and presentation abilities written and verbal to all level of an organization
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