Machine Learning (Internship)

DESCRIPTION

Are you tired of shopping for clothes and finding that the models look nothing like you?  Are you sick of hearing people talk about inclusion and diversity without taking action? Are you ready to disrupt an industry and be a pioneering link between FASHION and Generative AI? 

Do you want to join an ambitious and international team? Do you enjoy experimenting with cutting-edge technology?  Are you looking forward to working closely with Machine Learning (ML) experts? 

If so, we offer you the chance to join an international and multi-disciplinary team working in an innovative start-up environment with a lot of freedom and responsibility, where you will be guided by our experienced team members. We will coach and guide you during the internship. You will support the team building end-to-end data-driven AI solutions. You should feel comfortable with quick prototyping Python scripts, build simple ML algorithms and manage data.

WHAT CAN YOU EXPECT:

Working at Lalaland is all about giving you opportunities to showcase your skills and develop new ones. With an encouraging and innovative environment, get ready to be involved in the development of cutting-edge AI solutions to disrupt the global market. At Lalaland you learn and grow, not only professional, but also as a person. We truly believe in transparency and accountability

KEY RESPONSIBILITIES INCLUDE BUT ARE NOT LIMITED TO:

• Study/review existing literature on ML/Deep Learning for automatic features extraction and classification of features like ethnicity, age, skin colour, hair type, amongst others human-body features from imagery.
• Perform experiments to identify human features using state-of-the-art techniques.
• Share and document the literature review, the experiments, and the results of the investigations.

REQUIREMENTS & QUALIFICATIONS:

1. You are enrolled in a relevant field of education, such as but not limited to Computer Science, AI or similar fields.
2. You are currently pursuing a Master’s degree.
3. Previous exposure to ML in general and/or familiar with Deep Learning-based models.
4. Experience with Python.
5. Fluent in English (Dutch is not required).

NICE TO HAVE:

• Experience in data/feature engineering is a plus.
• Exposure to cloud providers like AWS or Azure is a plus.
• Experience with object detection, image segmentation or classification methods is a plus.
• Experience with TensorFlow, fast.ai, Pytorch, Keras, Scikit-learn, Open-cv, Scikit-image or similar libraries/frameworks is a big plus.