Machine Learning Engineer

Intel
Hillsboro, OR 97123
  • Job Code
    JR0178994
Job Description

Builds machine learning based products/solutions, which provide descriptive, diagnostic, predictive, or prescriptive models based on data. Uses or develops machine learning algorithms, such as supervised and unsupervised learning, deep learning, reinforcement learning, Bayesian analysis and others, to solve applied problems in various disciplines such as Data Analytics, Computer Vision, Robotics, etc. Interacts with users to define requirements for breakthrough product/solutions. In either research environments or specific product environments, utilizes current programming methodologies to translate machine learning models and data processing methods into software. Completes programming, testing, debugging, documentation and/or deployment of the solution/products. Engineers Big Data computing frameworks, data modeling and other relevant software tools.

 

The ideal candidate must possess the following behavioral traits:

  • Sustained demonstration of prioritizing objective decision making, developing technical talent, fostering a culture of inclusion and empowerment of others' success, and building trust and followership.

  • Unafraid of taking risks, failing fast, and role modeling.

  • Accountability/accepting failures and learning from it

  • Oral and communication skills to articulate complex technical and business issues and solutions to varied audiences of technical experts and managers at multiple levels.

  • Demonstrated flexible intellect and ability to move from strategic focus to the management of tactical detail while simplifying complex and conflicting tasks and policy positions


Qualifications

You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates

Minimum Qualifications:

  • PhD in Science, Engineering, Math with predominant emphasis on modeling/algorithms in complex technology/manufacturing environment.

  • 10+ years of experience in developing and applying advanced algorithms across multiple industries and domains.

  • 10+ years of experience applying a variety of parametric/non-parametric, time-series, NN, supervised/unsupervised, Bayesian ML techniques to varied problems.

  • 10+ years of proven track record of leading and solving tough technical problems, while creating and capturing business value.

  • 10+ years with various data types: time series, image, numeric and text. Skillful in both big data analytics with Hadoop/Spark and small data modeling using advanced statistical approaches.

  • 5+ years of programming experience in Python/R and thorough knowledge on advanced data structures. Experience with Java/Scala/C++ preferred.

 

Preferred Qualifications:

  • Knowledge of yield modeling and process flow in semiconductor manufacturing.

Inside this Business Group

As the world's largest chip manufacturer, Intel strives to make every facet of semiconductor manufacturing state-of-the-art -- from semiconductor process development and manufacturing, through yield improvement to packaging, final test and optimization, and world class Supply Chain and facilities support. Employees in the Technology and Manufacturing Group are part of a worldwide network of design, development, manufacturing, and assembly/test facilities, all focused on utilizing the power of Moores Law to bring smart, connected devices to every person on Earth



Posting Statement

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.

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Machine Learning Engineer

Intel
Hillsboro, OR 97123

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