Machine Learning Intern
In this position, you will join the loadmaster.ai ML team which is focused on developing, implementing and integrating state-of-the-art Reinforcement Learning (RL) models to optimise container terminal operations. We use RL algorithms to enhance efficiency and decision-making across a variety container terminal scenarios. As part of this journey, you’ll help tackle the unique challenges involved in building, training, and deploying RL models, the simulation environment used to train the RL models and how to demo this to clients.
What will you do?
Your primary responsibility will be to support the development and optimisation of our simulation and training platform including the development of a demo pipeline for potential clients. Our RL agents train within a simulator (a digital twin of the container terminal), exploring millions of scenarios to learn optimal container management strategies. The simulator is a central part of our training infrastructure and therefore has to be faithful to reality and fast to train on. You will be working on a range of tasks, including, but not limited to:
- Developing simulator components: contribute to building modules in our container terminal simulator to ensure fast and realistic training runs for our agents
- Optimising infrastructure: Working on optimisations to our simulators and broader training infrastructure to make training faster and improve our experiment tracking
- Working with real-world datasets to improve our domain understanding
- Train state-of-the-art algorithms to improve the performance of the RL model
- Explore alternative approaches to optimising container terminals (e.g., Linear programming, genetic algorithms)
- Design and implement a demo/POC pipeline for our products
Since our solutions are actively deployed, you’ll also participate in brainstorming sessions and collaborate with our team to ensure that we implement the most efficient and impactful solutions. Being a team player with strong communication skills is critical, as you’ll work closely with both your colleagues and our clients to develop practical, performance-driven models. You’ll be working in a small team so initiative and proactiveness are essential. You’ll be encouraged to try new ideas, and steer the internship toward topics that interest you most.
What do we require?
- Pursuing or completing an MSc in a technical subject, with a focus on RL
- Demonstrated knowledge in Al. Knowledge of Reinforcement Learning is a big plus
- Development experience in Python and familiarity with best practices in software engineering
- An knack for writing clean and optimised code
- Experience with popular machine learning frameworks (e.g., PyTorch/Tensorflow) and data science tools (e.g., Numpy and Pandas)
- Excellent communication skills
- Available for at least 4 months
What do we have to offer?
Being a small team, we still have the special start up/scale up vibe. However, we are growing fast, and with this growth, we face many challenges. This also gives you the opportunity to be part of that growth through your internship to kick-start your career.
At loadmaster, we believe that our customers will need a long term partnership for their digitization and process optimization. That results in a variety of problems thrown at us, and thus a very dynamic environment. No two weeks will be the same.
The start of the internship can be flexible. It can be done full time or 4 days a week part-time, combined with your thesis or studies. The place of work will be Marconiplein 16 Rotterdam in the Netherlands and has to be physical for at least 2 days a week. We will pay you a monthly stipend. If we’re a good match, we’ll consider you for a full-time role following the internship.
For internships, we only do one round of interviews.
About us
loadmaster.ai is part of frontiergroup.ai frontiergroup.ai is a holding company which includes initiatives like loadmaster. While each initiative is its independent company we all share resources. Expect to interact with people working on completely different projects to you. In general, we have a relaxed and friendly culture and strive for continual growth as individuals and as a company, together.
We hope to see you soon!
