- Enrolled in a PhD degree program in Computer Science, Computer Engineering, or any related field (at least 1 year remaining as an active student).
- 1+ year of experience working with applied machine learning towards audio-related applications such as Tensorflow, Caffe, Keras, SKlearn, Pandas.
- 1+ year of experience coding in Python.
- Intermediate to advanced English level.
- Must have unrestricted - permanent right to work in Mexico.
- 2 years remaining as an active student.
- 1+ year of experience coding in C++, C or Matlab.
- Experience in Pytorch or a similar deep learning framework.
Job Type:
Student / Intern Shift:
Shift 1 (Mexico) Primary Location:
Mexico, Guadalajara Additional Locations: Business group:
Intel Labs is the company's world-class, industry leading research organization, responsible for driving Intel's technology pipeline and creating new opportunities. The mission of Intel Labs is to deliver breakthrough technologies to fuel Intel's growth. This includes identifying and exploring compelling new technologies and high risk opportunities ahead of business unit investment and demonstrating first-to-market technologies and innovative new usages for computing technology. Intel Labs engages the leading thinkers in academia and industry in addition to partnering closely with Intel business units. 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.
Position of Trust
N/A Work Model for this Role
This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. In certain circumstances the work model may change to accommodate business needs.