机器学习研究员

Nex is on a mission to help families rediscover the joy of movement. Created by parents for parents, Nex combines technology and play to deliver fun, social, and interactive experiences powered by natural body motion, encouraging kids and adults to move more, play more, and have fun together. Nex Playground, the company’s award-winning active play system, is purpose-built to get families moving year-round, with safety and privacy as core considerations in its intentional design. It is certified kidSAFE+ COPPA compliant and built to support healthy, active play for all ages and abilities.

Nex Playground features a growing library of 50+ experiences, including motion and dance games, fitness and educational experiences, and Nex Originals. Content includes collaborations with partners like Hasbro, Sesame Workshop, and NBCUniversal. Nex has been recognized by Fast Company’s Most Innovative Companies, TIME’s Best Inventions, and Parents’ Best Entertainment System for Families, and has earned Red Dot, IDEA, and Core77 international design awards. We encourage you to explore Have Fun and Is Motion Gaming Back?, as they offer a deeper look into our culture, values, and explain how our approach to motion gaming differs from previous generations.

To protect yourself from recruitment scams, please note that Nex communicates through official company emails ending in @nex.inc. If you receive a suspicious email or message, please do not respond and report it immediately to us.

Location: Hong Kong or Remote
Type: Full Time

The Role

As a ML Researcher at Nex, you will develop new machine learning models and algorithms that push the boundaries of computational perception and interaction on Nex Playground. You will join a small, deeply technical team that combines research and engineering to solve complex problems in sensing, understanding, and multimodal interaction.

The ML Research role emphasizes rapid experimentation, exploring new ideas and methods to expand what our platform can sense, understand, and respond to. You will work within the ML Research group, collaborating closely with ML Engineers who build the infrastructure that accelerates your research.

This role is ideal for researchers who want to see their work directly impact product capabilities while maintaining a focus on cutting-edge innovation.

The Mindset

You are driven by curiosity and technical discovery. You see research as a systematic process of exploration and validation, not just theoretical work. You balance scientific rigor with practical impact, knowing that the best research solves real problems. You thrive in a team that values experimentation velocity and measurable technical improvement.

What You’ll Do

• Develop novel ML models and algorithms for computational perception and interaction

• Design and execute rapid experiments to validate new ideas and methods

• Explore advancements in computer vision, audio processing, sensor fusion, or related domains

• Collaborate with ML Engineers to integrate research outcomes into training pipelines and production systems

• Measure and track experimentation velocity, the number and quality of validated experiments per quarter

• Contribute to research planning and help define the technical roadmap alongside the Engineering Manager and Tech Lead

• Document research findings and communicate technical progress to the broader team

Must Have

• 2+ years of hands-on ML research experience in industry, academia, or research labs

• Demonstrable track record of designing and conducting ML experiments from hypothesis to validation

• Proficiency in Python for ML research and experimentation

• Deep expertise with PyTorch or TensorFlow for model development

• Experience training and evaluating ML models on real datasets

• Understanding of model evaluation metrics, experimental design, and statistical validation

• Familiarity with data preprocessing, augmentation, and management for ML workflows

• Experience presenting research findings to technical audiences

Nice To Have

• Expertise in real-time inference, model optimization, or efficient architectures

• Experience with self-supervised learning, few-shot learning, or foundation models

• Background in multimodal learning combining vision, audio, and sensor data

• Contributions to open-source ML projects or released research code

• Experience collaborating with engineers to productionize research outcomes

• Familiarity with ML Engineering practices: training pipelines, experiment tracking, MLOps

• Background in edge computing, on-device ML, or resource-constrained environments

• Experience with sensing technologies: cameras, microphones, IMUs, or haptic systems

• Knowledge of privacy-preserving ML, federated learning, or on-device data processing

We Offer

• Competitive compensation package.

• Flexible working hours and vacation policy.

• Product-driven culture that treasures talents and individual growth.

• Front-row seat and hands-on experience with cutting edge technologies in the evolving gaming field

Nex is located in San Jose, California, USA and Hong Kong. Learn more about us at https://www.nexplayground.com/about.

We encourage applications even if you don’t meet more than 50% of the requirements — we believe that experience comes in many forms!

Nex is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, gender identity, and sexual orientation), national origin, ancestry, age, physical or mental disability, medical condition, genetic information, marital status, military or veteran status, or any other characteristic protected by applicable law. This policy applies to all individuals at every stage of the employment relationship, including all current and prospective employees, and covers all employment decisions including recruitment, hiring, job assignment, promotion, compensation, benefits, training, discipline and termination.

We are committed to providing a workplace free from discrimination and harassment and to fostering an inclusive environment for all employees.