Responsibilities
- Design and manage search recommendation services and models to support the content team, empowering content ecosystem development.
- Utilize machine learning-based personalization methods, design patterns, and tools to enhance content matching and distribution efficiency.
- Deep understanding of recommendation systems within the content domain, leveraging business knowledge to drive AI product upgrades and improve content experience and business outcomes.
- Lead the development of core content recommendation modules using data-driven strategies to maximize content value and user impact.
- Collaborate with content, business, and product management teams to identify needs and opportunities within content scenarios, and jointly define success metrics.
Requirements
- MSc or PhD in Machine Learning, Computer Vision, Computer Science, or Applied Mathematics, with at least 5 years of relevant industry experience (experience in the content domain is preferred).
- Strong hands-on experience with popular machine learning frameworks such as PyTorch or TensorFlow.
- Experience in large-scale application development, preferably in content-related user-facing applications.
- Excellent cross-team collaboration skills with the ability to work effectively with global content teams.
Nice to Have
- Publication record at top-tier conferences or journals is a plus.
Benefits
- Be a part of the world’s leading blockchain ecosystem that continues to grow and offers excellent career development opportunities
- Work alongside diverse, world-class talent in an environment where learning and growth opportunities are endless
- Tackle fast-paced, challenging and unique projects
- Work in a truly global organization, with international teams and a flat organizational structure
- Competitive salary and benefits
- Flexible working hours, remote-first, and casual work attire
- Competitive salary and company benefits
- Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)
Additional Information
- Flexible working hours
- Remote-first
- Casual work attire
- Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)
