Why This Traineeship?
Our traineeships are continuously incorporating the latest market developments. We also optimize our newest programs by including experiences from the previous traineeship; each training program is better than the last. You will complete the training adept with the most relevant and technologically advanced skill sets.
The traineeship starts with eight weeks of full-time education at our home office. For eight weeks, we immerse you in our world of machine learning engineering with intensive classes and coaching by our team of experienced trainers. Through rigorous training with an emphasis getting familiar with state-of-the-art tooling you will start your next project ahead of the curve. Your ability to bring your machine learning models into production will make you stand out with clients.
Starting a new assignment can feel overwhelming. Collaborating with new colleagues, juggling deadlines, and considering all stakeholders and perspective can be be a lot to take in. Knowing we have your back will make all the difference. Our veteran data expert’s extensive guidance will help you navigate your projects and challenges. It doesn’t hurt they’re pretty great people too.
Collaborating and growing alongside fellow data trainees will allow you to become an integral part of Aurai’s network. You will get to know many other ambitious data experts on your journey to becoming a certified machine learning engineer. Your coach will be an experienced engineer who has trained many professionals of varying levels. You’ll be in good hands. Our Slack channel is open for questions and will help guide you through this exciting process.
Our machine learning engineering traineeship will prepare you to be optimally deployed in any team at any time – operating at the frontline of the latest data developments. As Aurai’s machine learning engineering trainee you will learn to use the Cloud to design, build and maintain data pipelines. Join our traineeship and become adept in bringing your machine learning models into production.