Summer 2027 | Software Engineer Intern (ML Research, Core Technology)

The Core Technology team develops the technologies that allow Nex Playground to use cameras, microphones, and other sensors to understand player movement and interactions in real time.

As our Software Engineer Intern (ML Research, Core Technology), you will explore and develop machine learning methods that expand what Nex Playground can perceive and understand. You may work on computer vision, audio, sensor fusion, or other sensing problems, taking ideas from research hypotheses through experimentation, evaluation, optimization, and working prototypes.

You will collaborate with ML researchers and software engineers to build datasets and experimental workflows, evaluate ideas rigorously, and demonstrate promising technologies under real-world and on-device constraints. You will receive hands-on mentorship while owning a meaningful research project that contributes to our future products and technical direction.

• →Develop and evaluate ML models and algorithms for computational perception and interaction.
• →Design rigorous experiments, improve datasets, compare approaches, and understand failure modes.
• →Build training and evaluation tools, and optimize promising models for real-time, on-device inference.
• →Collaborate with researchers and engineers to prototype technologies on Nex Playground and communicate your findings.

• Must be currently enrolled in an undergraduate or graduate degree program at an accredited college or university.
• Strong interest in machine learning and enthusiasm for learning new methods and tools.
• Solid mathematical fundamentals and comfort with quantitative reasoning.
• Strong analytical and problem-solving skills.
• Programming experience in any language.
• A curious, systematic approach to learning through experimentation.
• Strong communication and collaboration skills.

• Experience with Python or familiarity with PyTorch, TensorFlow, or another ML framework.
• Interested in computer vision, audio processing, sensor fusion, or multimodal learning.
• Interested in model optimization, on-device inference, GPUs, NPUs, or resource-constrained devices.
• Interested in data curation workflows, or dataset quality analysis.
• Enthusiastic about games, interactive physical experiences, and helping people be active and healthy.