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Pearson Senior Machine Learning Engineer in San Jose, California

Senior Machine Learning Engineer

Description

At Pearson, we’re committed to a world that’s always learning and to our talented team who makes it all possible. From bringing lectures vividly to life to turning textbooks into laptop lessons, we are always re-examining the way people learn best, whether it’s one child in our own backyard or an education community across the globe. We are bold thinkers and standout innovators who motivate each other to explore new frontiers in an environment that supports and inspires us to always be better. By pushing the boundaries of technology — and each other to surpass these boundaries — we create seeds of learning that become the catalyst for the world’s innovations, personal and global, large and small.

The Personalized Learning and Analytics team (PLA) in Pearson is responsible for software development of analytics and machine learning platforms. PLA is growing and we are looking for a new team member to build a machine learning solution for Pearson’s Global Learning Platform (GLP). Together with a highly multi-disciplinary team of engineers, data scientists, strategic partners, product managers and subject domain experts you will work on building adaptive solutions powered by big data. You will work on a best-in-class cloud computing platform, with cutting edge big data tools at your disposal while having access to experts in education, engineering and data science.

Pearson is an Equal Opportunity and Affirmative Action Employer, and a member of E-Verify. All qualified applicants, including minorities, women, veterans, and people with disabilities are encouraged to apply.

RESPONSIBILITIES:

  • 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 road map

  • Work closely with engineers to build, test, deploy and troubleshoot machine learning / algorithm based software

Qualifications

QUALIFICATIONS:

  • 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, Tensor flow, scikit-learn, MLib, DLib, Pandas or others like H2O, Databricks

PREFERRED QUALIFICATIONS:

  • Familiar with industry standard software engineering practices using CI/CD tools and infrastructure with a working knowledge of Unix/Linux systems

  • Experience with working on large data sets, especially with Hadoop and Spark

  • Experience with cloud computing platforms such as AWS

Pearson is an Equal Opportunity and Affirmative Action Employer and a member of E-Verify. All qualified applicants, including minorities, women, protected veterans, and individuals with disabilities are encouraged to apply.

Primary Location: US-CA-San Jose

Work Locations: US-CA-San Jose-303 Almaden 303 Almaden Boulevard Suite 500 San Jose 95110

Job: Technology

Organization: Global Product

Employee Status: Regular Employee

Job Type: Standard

Shift: Day Job

Job Posting: Jul 11, 2019

Job Unposting: Ongoing

Schedule: Full-time Regular

Req ID: 1908844

Pearson is an Equal Opportunity and Affirmative Action Employer and a member of E-Verify. All qualified applicants, including minorities, women, protected veterans, and individuals with disabilities are encouraged to apply.

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