Machine Learning Engineer intern
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YOUR MISSION AT VOI
As a Machine Learning Engineer Intern at Voi, you will play a key role in designing and building machine learning models for our edge ML product. You will work across both software engineering and machine learning challenges, contribute to our product rollout, and help enhance the safety and real-world performance of our vehicles. You will join a high-impact product team, see your work deployed on Voi vehicles worldwide, and learn how to build ML products end-to-end.

In this role, you will:

• Help build a cutting-edge machine learning product and see your models deployed on Voi vehicles across multiple markets.
• Build an ML solution end-to-end, from dataset creation and PoC model development to edge ML optimisation, deployment and impact measurement.
• Support production-grade models with a focus on reliability, scalability, and high performance.
• Collaborate with a world-class, cross-functional product team, aligning on priorities and outcomes while learning from and supporting your teammates.

WHAT YOU NEED TO EMBARK
You are a curious, hands-on and analytical problem-solver with a strong interest in applied machine learning. You enjoy working with real-world data, building models that ship to production, and collaborating with others to create solutions that make a tangible impact.

We believe you have:

• Current enrolment in an MSc in Computer Science, Machine Learning, Robotics or a related field, with around one year or less remaining in your studies.
• Strong Python programming skills and experience with Git; experience deploying machine learning models or backend code in production is a plus.
• Solid understanding of common machine learning techniques such as convolutional neural networks, transfer learning and object detection, and hands-on experience with frameworks such as PyTorch, TensorFlow or scikit-learn.
• Fluency in written and spoken English, and a proactive communication style in a cross-functional team environment.

Don’t meet every requirement? If you are excited about this role and our mission, and have relevant, transferable skills, we encourage you to apply – even if you don’t check every box.