Machine Learning Engineer Lead (Feed/ Content Recommendation)

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.
Data-driven based business is the core in helping us to use the cloud-native platforms to serve tens of millions of crypto-currency users. Engineers and Data Scientists across the company use the data platform to do interesting and impactful analyses for continuous innovations. As a data scientist, you will have the opportunity to leverage rich data (PB-level scalability) and state-of-art machine learning infrastructure to develop data products that are used by our tens of millions of crypto-currency users. You will collaborate with a strong team of engineers, data analysts, business operation and product/marketing managers to define and build solutions, features, algorithms and products based on our rich data and cutting-edge machine learning technology.     We have multiple openings available and many more are coming due to our rapid growth of the business. Sample projects include:   - Personalized recommender system: leverage of our PB-scale data warehouse to perform in-depth analysis and recommender system for our end-users - Data driven customer feedback and satisfaction analysis: leverage of machine learning techniques to understand customer’s feedback and satisfaction with proven data evidence and analysis   To be successful in this role, you MUST be a quick learner, stellar machine learning skills with rich and solid experience from inception to business impact, strong communication capabilities and work well in cross-functional teams (e.g. with data users from different marketing and consumer team).   This is a great opportunity to enhance your machine learning /data science skills in markets and familiarize with Blockchain based technology and etc while making a real impact on Blockchain and Crypto-Currency technology globally.

Responsibilities

Responsible for designing and managing search recommendation services and models

using AI to create truly personalized recommendations and address our customers’ queries and intent

Knowledge of machine learning powered personalization methods, design patterns and tools

In-depth understanding of Recommendation systems with the business domain knowledge to take the impact of AI product to the next level

Drive the development of core modules with data-driven strategy to maximize the impact

Identify the needs and opportunities, define success metrics with Business and Product management teams

Requirements

MSc or Phd in Machine Learning, Computer Vision, Computer Science or Applied Mathematics with at least 5 years of relevant industry experience

Excellent hands-on experience with popular Machine Learning frameworks such as PyTorch or TensorFlow

Fluent in English, both written and spoken

Experience with application development practices at scale

Good global team collaboration skills and experiences are good add-ons as well

Publication record at top conferences and journals is a plus

 Why Binance• Shape the future with the world’s leading blockchain ecosystem• Collaborate with world-class talent in a user-centric global organization with a flat structure• Tackle unique, fast-paced projects with autonomy in an innovative environment• Thrive in a results-driven workplace with opportunities for career growth and continuous learning• Competitive salary and company benefits• Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)
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