Technical lead for ML-Ops; Develop and manage ML infrastructures and CICD pipelines to support multiple data products; Provide engineering mentorship and guidance to data-scientists; Collaborate with ML engineers, data scientists, data engineers, and product and operation teams; Develop, integrate, and optimize end-to-end AI pipelines by a data-driven approach; Build fully automated, scalable, cost-effective, and fault-tolerant solutions in AWS to process billions of records; Collaborate with data quality teams to build data annotation/evaluation pipelines, monitoring, and dashboards
Requirements:
Strong collaboration skills as well as verbal and written communication skills; Professional in ML Operationalization, including workflow/model management platforms such as Airflow/MLflow; 4+ years of experience in professional software development; 2+ years of experience as a Machine Learning Engineer or relevant jobs; 2+ years of experience in cloud development; Solid programming skills in Python
Text:
Senior Machine Learning Engineer Technical lead for ML-Ops; Develop and manage ML infrastructures and CICD pipelines to support multiple data products; Provide engineering mentorship and guidance to data-scientists; Collaborate with ML engineers, data scientists, data engineers, and product and operation teams; Develop, integrate, and optimize end-to-end AI pipelines by a data-driven approach; Build fully automated, scalable, cost-effective, and fault-tolerant solutions in AWS to process billions of records; Collaborate with data quality teams to build data annotation/evaluation pipelines, monitoring, and dashboards Strong collaboration skills as well as verbal and written communication skills; Professional in ML Operationalization, including workflow/model management platforms such as Airflow/MLflow; 4+ years of experience in professional software development; 2+ years of experience as a Machine Learning Engineer or relevant jobs; 2+ years of experience in cloud development; Solid programming skills in Python
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