Machine Learning Engineer
- Silicon Valley, CA, United States
- $140k - $170k
- 0.0% - 8.0%
- React Native
- Spring MVC
Pearson has one defining goal: to help people progress in their lives through learning. We champion innovation and we invest in models for education that deliver on our promise for effective, accessible, and personal learning from early literacy, college and career readiness to professional education, through data informed instruction and inventive applications for mobile and digital learning.
Pearson, the world's leading learning company, has global-reach and market leading businesses in education, business, and consumer publishing and is listed on the London and New York stock exchanges (UK: PSON; NYSE: PSO). For more information, visit www.pearson.com.
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: - 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
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.
Our capabilities are based on our deep expertise in how people learn, and we apply them to our three strategic priorities:
Grow market share through the digital transformation of our courseware and assessment businesses by shifting from selling ownership of our content to selling print or digital services. Invest in structural growth opportunities that promote lifelong learning, such as professional certifications and licensure, virtual schools, online program management, and English language learning and assessment. Become a simpler, more efficient, and sustainable company by eliminating duplication, increasing standardization, and improving access to and outcomes for our products.
Our Culture These define the culture of our organization and fortify the way we do business.
Bravery Bravery means publishing books and reporting news with impartiality, accuracy, and integrity. It also means moving courageously forward with the confidence of a world leader and the vision of a start-up that is re-inventing education around the globe. Bravery means driving change, transforming learning, and hiring bold thinkers and standout innovators who motivate each other to explore new frontiers.
Decency We are committed to: supplying the highest possible quality of product and service to our customers; supporting charitable endeavors that advance literacy, learning, and teaching; and offering careers that meet our employees desire to fulfill a higher calling. Pearson People display a very strong sense of interpersonal respect and gentility that is an outflow of being grounded in our education and teaching environment. We are also responsible stewards of our environment and our finances, and maintain a steady, pragmatic approach to the constant change our growth is creating.
Imagination Even though we are a company dedicated to facts and knowledge, it’s our imagination that drives us forward. Our company is growing and transforming in new and exciting ways because of a vision to enhance the learning movement across the globe. This is a pivotal time for new ideas that disrupt the status quo and take us through a time of change to an unprecedented future together.
- React Native
- Spring MVC
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