Model Validation Jobs in Richmond, VA

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Distinguished Applied Researcher  

Capital One - Richmond, United States

Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development

from: us.lifeworq.com - 3 days ago

Applied Researcher I  

Capital One - Richmond, United States

the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage

from: us.lifeworq.com - 3 days ago

Manager, Data Scientist - Compliance Risk  

Capital One - Richmond, United States

huge volumes of numeric and textual data Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation Flex your interpersonal Competitive

from: efinancialcareers.com - 10 days ago

Applied Researcher II  

Capital One - Richmond, United States

the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage

from: us.lifeworq.com - 3 days ago

Sr. Director, Applied Research  

Capital One - Richmond, United States

, and more — to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation

from: us.lifeworq.com - 3 days ago

model risk specialist  

Randstad - glen allen, virginia

Allen, Virginia job type: Contract salary: $40 - 52 per hour work hours: 9am to 5pm education: Doctorate responsibilities: · Conduct independent model validations from inception (scoping, project $40 - $52 per hour

from: randstadusa.com (+1 source) - 24 days ago

Senior Manager, Machine Learning Engineering  

Capital One - Richmond, United States

, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment

from: us.lifeworq.com - 3 days ago


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