AI Career Program for University Graduates
What is this program?
We’re looking for students and recent graduates who are seeking career opportunities in the field of AI. We’d like to learn what you’re looking for in your next opportunity, and match you with roles available in our affiliated communities.
Depending on your background and type of role you are interested in, three tracks are available:
- Machine Learning Engineer
- Data Scientist
- Software Engineer
All tracks will give you privileged access to our network of high-quality AI teams in various international locations. These include applied engineering teams in Education, Manufacturing, Healthcare, Autonomous Driving, Energy, Transportation, Robotics, Social Media, FinTech, Agriculture and more.
Who should apply?
If you’re a student (or recent grad) interested in joining an AI team as a Machine Learning Engineer, Data Scientist, Software Engineer or Researcher, we’d like to hear from you. That means you’re probably familiar with some of the following:
- Machine learning. You should be able to understand and apply major machine learning methods, such as logistic regression, SVM, Decision Trees, Principal Component Analysis and K-means. Completion of Andrew Ng’s Machine Learning course on Coursera is sufficient to meet this criterion.
- Deep learning. You should be able to understand and apply major deep learning methods, including neural network training, regularization, optimization methods (gradient descent, Adam), and be familiar with major neural network architecture types such as Convolutional Networks, RNN/LSTM. Completion of the deeplearning.ai specialization is sufficient to meet this criterion.
- Implementation. You should have prior experience taking a dataset, cleaning it if necessary, and applying a learning algorithm to it to get a result. You should be able to implement a learning algorithm “from scratch” using a framework such as NumPy, Tensorflow, Pytorch, Caffe, etc.
- General coding. You should be able to code non-trivial functions in object-oriented programming, such as popular sorting or search algorithms.
- Mathematics (including probabilities and statistics.) You should be able to use mathematical notations and linear algebra (matrix/vector operations, dot products, etc.), and understand basic probability theory (distributions, independence, density functions, etc.) as well as statistics (mean, variance, median, quantiles, covariance, etc.)
- Software Engineering. You should know how to use your terminal, work with version control systems (Git), relational databases, APIs, and build the back-end of web or mobile applications.
Apply below to join this program and select your track(s):