Hypotenuse AI – Machine Learning Engineer Intern

At Hypotenuse AI, we're building the best shopping experience to power every e-commerce store. We are a Y Combinator-backed machine learning start-up that automatically generates written content for e-commerce companies, including product descriptions, advertising text and headlines.

We are a passionate team with experienced founders from a background in big tech companies, AI research and e-commerce. We have global ambitions and are expanding our team in Singapore. If you are inspired to take up new challenges to drive the future of e-commerce and content, come join our team! More about us on TechCrunch.

At Hypotenuse, interns aren’t here to do paperwork or monotonous tasks. We empower you to make decisions, contribute creatively and think critically. We want self-starters who are entrepreneurial and want a taste of working in a high-growth, fast-moving start-up.

As an ML Engineer intern at Hypotenuse, you will get hands on experience in designing and implementing state-of-the-art machine learning models for computer vision and NLP while receiving direct mentorship.

Responsibilities include:

• Ownership in designing, implementing, validating and deploying deep learning models for computer vision and NLP
• Communicate with different company functions to understanding the problem and solution space and its requirements
• Build, run and extend on experiments with cutting edge research in machine learning to solve real-world problems in e-commerce
• Write neat and maintainable code of high quality
• Contribute to engineering efforts to build scalable production ML systems

Requirements:

• Passionate about applied machine learning and its use to solve complex real world problems
• Project or work experience in designing, training and validating deep learning / neural network-based architectures in any application (e.g. computer vision, NLP, graphs, tabular data, speech)
• Strong proficiency in one or more programming languages, ideally with Python being one of them
• Experience with any deep learning framework (e.g. Pytorch, Tensorflow, MxNet..)
• Ideally, experience in building, deploying, and improving Machine Learning models and algorithms in real-world products — including GPU training and model serving
• Relevant work experience in machine learning software development and architectures for machine learning is a plus.
• Excellent verbal and written communication skills; ability to convey complex concepts simply