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 companys 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 Companys Most Innovative Companies TIMEs 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 FunandIs 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.
Location: Hong Kong / 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 Youll 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 experiencein industry academia or research labs
- Demonstrable track record ofdesigning and conducting ML experimentsfrom hypothesis to validation
- Proficiency in Pythonfor ML research and experimentation
- Deep expertise withPyTorch or TensorFlowfor model development
- Experiencetraining and evaluating ML modelson real datasets
- Understanding ofmodel evaluation metrics experimental design and statistical validation
- Familiarity withdata preprocessing augmentation and managementfor ML workflows
- Experiencepresenting research findingsto technical audiences
Nice To Have
- Expertise inreal-time inference model optimization or efficient architectures
- Experience withself-supervised learning few-shot learning or foundation models
- Background inmultimodal learningcombining vision audio and sensor data
- Contributions toopen-source ML projectsorreleased research code
- Experience collaborating withengineers to productionize researchoutcomes
- Familiarity withML Engineering practices: training pipelines experiment tracking MLOps
- Background inedge computing on-device ML or resource-constrained environments
- Experience withsensing technologies: cameras microphones IMUs or haptic systems
- Knowledge ofprivacy-preserving ML federated learning or on-device data processing
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 Playgrou...
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 companys 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 Companys Most Innovative Companies TIMEs 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 FunandIs 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.
Location: Hong Kong / 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 Youll 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 experiencein industry academia or research labs
- Demonstrable track record ofdesigning and conducting ML experimentsfrom hypothesis to validation
- Proficiency in Pythonfor ML research and experimentation
- Deep expertise withPyTorch or TensorFlowfor model development
- Experiencetraining and evaluating ML modelson real datasets
- Understanding ofmodel evaluation metrics experimental design and statistical validation
- Familiarity withdata preprocessing augmentation and managementfor ML workflows
- Experiencepresenting research findingsto technical audiences
Nice To Have
- Expertise inreal-time inference model optimization or efficient architectures
- Experience withself-supervised learning few-shot learning or foundation models
- Background inmultimodal learningcombining vision audio and sensor data
- Contributions toopen-source ML projectsorreleased research code
- Experience collaborating withengineers to productionize researchoutcomes
- Familiarity withML Engineering practices: training pipelines experiment tracking MLOps
- Background inedge computing on-device ML or resource-constrained environments
- Experience withsensing technologies: cameras microphones IMUs or haptic systems
- Knowledge ofprivacy-preserving ML federated learning or on-device data processing
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