Internship Position in Machine Learning

altair_logoJob Description:

We are looking for an intern that will lead a benchmark of machine learning algorithms for engineering applications; specifically related to digital twin and predictive maintenance.

Founded in 1985, Altair is headquartered in Troy Michigan with regional operations throughout 22 countries and provides software and services to over 5,000 corporate clients representing the automotive, aerospace, government and defense, and consumer products verticals. Altair also has a growing client presence in the electronics, architecture engineering and construction, and energy markets.

Altair prides itself on its business culture that enables open, creative thinking, deeply valuing our employees and their individual contributions towards our clients’ success as well as our own each and every day. There is an entrepreneurial spirit that flows and is encouraged throughout our global workforce to develop and gather technology that is relevant to engineering and business – including employing it within our own organization.

In this position, you will be working with a team of engineers, computer scientists and mathematicians that has over 25 years of experience in developing and applying predictive and prescriptive analytics to a variety of applications including but not limited to mobile phones, planes, bikes, consumer products, whitegoods and automobiles.

The outcome of this project will shape Altair’s offerings in emerging domains such as predictive maintenance, digital twin and autonomous vehicles.


Altair headquarter building in Troy, MI; part-time telecommuting is acceptable.


1. Review public datasets and choose a subset to be used for benchmarking.
2. Review available predictive modelling/machine learning tools and identify the ones to include in the benchmark.
3. Become familiar with the predictive modelling/machine learning implementations in Altair such as the ones in HyperStudy.
4. Conduct the benchmark for performance and accuracy
5. Make suggestions for methods and applications.


  • Graduate student in data science or related fields.
  • Bachelor of Science Degree in Mechanical Engineering, Aerospace Engineering, Materials Sciences or related fields.
  • Experience with data analysis and prediction modelling tools and languages such as R, Python, SAS, Matlab, Tableau, MicroSoft Azure.
  • Experience in engineering or scientific work is preferred.
  • Experience with machine learning, predictive and prescriptive modelling methods.
  • Excellent communication skills both written and verbal.
  • Good presentation skills.

Application procedures:

To apply please contactFatma Y. Koçer-Poyraz at