Hello,
Location - Minneapolis, MN(Remote)
Hire Type: Contract
Please do not share junior profiles for this position
10 + will Not work.
Job Summary
The Sr NLP Data Engineer is a key technical contributor in the design and development of data pipelines and data automations for training and monitoring models for machine learning medical applications. The Sr NLP Engineer works closely with software engineers, data scientists, and dev-ops engineers to ensure that data processes are repeatable and easily monitored in production.
Primary responsibilities include the enhancement of ETL pipelines, cloud automations, and experimental tracking and dashboard maintenance. Work will involve engineering focused tasks to support data acquisition and organization, as well as automation-focused work in cloud environments.
The successful candidate will have a strong background in Machine Learning Ops, with a focus on cloud platform integrations. The successful candidate will have proven success in supporting machine learning solutions in production environments. Strong technical skills are required.
Qualifications - Required Qualifications:
-- Undergraduate degree in a computational domain
-- 2+ years of related professional work experience working with ETL pipelines in cloud environments (AWS SageMaker, AzureML)
-- Experience with NLP - Required
-- Strength and experience with Python programming language and SQL query syntax
-- Experience with cloud computing processes in a clustered computing environment
-- Knowledge of algorithms and techniques within a computational domain with emphasis on text processing
Preferred Qualifications:
-- M.S. or PhD in a computational domain
-- Experience with PyTorch
-- Azure ML and/or AWS
-- Experience within the medical domain
Job Summary
The Sr NLP Data Engineer is a key technical contributor in the design and development of data pipelines and data automations for training and monitoring models for machine learning medical applications. The Sr NLP Engineer works closely with software engineers, data scientists, and dev-ops engineers to ensure that data processes are repeatable and easily monitored in production.
Primary responsibilities include the enhancement of ETL pipelines, cloud automations, and experimental tracking and dashboard maintenance. Work will involve engineering focused tasks to support data acquisition and organization, as well as automation-focused work in cloud environments.
The successful candidate will have a strong background in Machine Learning Ops, with a focus on cloud platform integrations. The successful candidate will have proven success in supporting machine learning solutions in production environments. Strong technical skills are required.
Qualifications - Required Qualifications:
-- Undergraduate degree in a computational domain
-- 2+ years of related professional work experience working with ETL pipelines in cloud environments (AWS SageMaker, AzureML)
-- Experience with NLP - Required
-- Strength and experience with Python programming language and SQL query syntax
-- Experience with cloud computing processes in a clustered computing environment
-- Knowledge of algorithms and techniques within a computational domain with emphasis on text processing
Preferred Qualifications:
-- M.S. or PhD in a computational domain
-- Experience with PyTorch
-- Azure ML and/or AWS
-- Experience within the medical domain
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