Robotics Prcocess Automation, LLC
Machine learning Engineer
Robotics Prcocess Automation, LLC, San Jose, California, United States, 95199
Job OverviewJob ID: J36993Specialized Area: Machine learningJob Title: Machine learning EngineerLocation: San Jose, CADuration: 8 MonthsDomain Exposure: Work Authorization: Client: To Be Discussed LaterEmployment Type: W-2 (Consultant must be on our company payroll. C2C is not allowed)- Developing scalable data processing pipelines for analytical and predictive platform services- Collaborate with other data scientists and engineers to find effective solutions to technical challenges- Provide recommendations, guidance, and options to support Pearson's GLP product development roadmap- Work closely with engineers to build, test, deploy, and troubleshoot machine learning/algorithm-based softwareQUALIFICATIONS:
- MSc or higher in computer science, statistics, mathematics, physical science, engineering, or a comparable related technical field- 5+ years of industry experience in engineering, data science, or related areas- Demonstrated mastery in communication of technical ideas to non-technical audiences- Ability to translate customer goals into practical engineering solutions- Good understanding of foundational statistics concepts and algorithms: linear/logistic regression, random forest, boosting, NNs, etc.- Strong programming skills with fluency in at least one of Python or R, Java, Scala, C/C++- Ability to access, manage, transfer, integrate, and analyze complex datasets, especially using SQL or map-reduce techniques- Familiarity with libraries such as Spark ML, TensorFlow, scikit-learn, MLib, DLib, Pandas, or others like H2O, Databricks
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- MSc or higher in computer science, statistics, mathematics, physical science, engineering, or a comparable related technical field- 5+ years of industry experience in engineering, data science, or related areas- Demonstrated mastery in communication of technical ideas to non-technical audiences- Ability to translate customer goals into practical engineering solutions- Good understanding of foundational statistics concepts and algorithms: linear/logistic regression, random forest, boosting, NNs, etc.- Strong programming skills with fluency in at least one of Python or R, Java, Scala, C/C++- Ability to access, manage, transfer, integrate, and analyze complex datasets, especially using SQL or map-reduce techniques- Familiarity with libraries such as Spark ML, TensorFlow, scikit-learn, MLib, DLib, Pandas, or others like H2O, Databricks
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