ML Researcher

This is a fully remote position, open to applicants in Hong Kong.

📋 Description

• Create innovative machine learning models and algorithms for computational perception and interaction.

• Design and implement swift experiments to validate fresh concepts and methodologies.

• Investigate developments in computer vision, audio processing, sensor fusion, or related fields.

• Work collaboratively with ML Engineers to incorporate research results into training pipelines and production systems.

• Measure and monitor experimentation velocity, including the quantity and quality of validated experiments each quarter.

• Assist in research planning and aid in defining the technical roadmap in conjunction with the Engineering Manager and Tech Lead.

• Record research outcomes and relay technical advancements to the wider team.

⛳️ Requirements

• A minimum of 2 years of practical ML research experience in industry, academia, or research laboratories.

• Proven ability to design and conduct ML experiments from hypothesis through to validation.

• Proficiency in Python for machine learning research and experimentation.

• Extensive expertise in PyTorch or TensorFlow for model development.

• Experience in training and assessing ML models using real datasets.

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

• Familiarity with data preprocessing, augmentation, and management for machine learning workflows.

• Experience in presenting research findings to technical audiences.

• Expertise in real-time inference, model optimization, or efficient architectures (Nice To Have).

• Experience with self-supervised learning, few-shot learning, or foundation models (Nice To Have).

• Background in multimodal learning that integrates vision, audio, and sensor data (Nice To Have).

• Contributions to open-source machine learning projects or released research code (Nice To Have).

• Experience working with engineers to transition research outcomes into production (Nice To Have).

• Familiarity with machine learning engineering practices such as training pipelines, experiment tracking, and MLOps (Nice To Have).

• Background in edge computing, on-device machine learning, or resource-constrained environments (Nice To Have).

• Experience with sensing technologies, including cameras, microphones, IMUs, or haptic systems (Nice To Have).

• Knowledge of privacy-preserving machine learning, federated learning, or on-device data processing (Nice To Have).

🏝️ Benefits

• Competitive compensation package.

• Flexible working hours and vacation policy.

• Product-driven culture that values talent and individual growth.

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