Senior Machine Learning Engineer
On-siteShenzhen Shenzhen, Guangdong, China
Job Summary
Leverage machine learning to enhance products and improve the shopping experience for users and merchants across recommendations, personalization, risk, fraud detection, and search. Navigate ambiguous problem definitions effectively with or without dedicated Product Manager support while driving efforts to positively influence critical business and product metrics. Foster a fast-paced, high-iteration experimental culture to test and refine solutions quickly, collaborating with cross-functional partners to set and achieve optimal outcomes. Maintain subject matter expertise in a specific ML domain while developing ML products with strong engineering practice and a mindset for scientific rigour at scale. Demonstrate the ability to develop ML products with good engineering practice and a mindset for scientific rigour at scale.
Required Qualifications
- Significant prior success as a Machine Learning Engineer working on challenging problems at scale
- 6+ years of industrial ML experience
- expertise in modeling and statistical modeling
- Good understanding of data collection, aggregation, analysis, visualization, productionisation, and monitoring of ML products - aka MLOps
- Ability to develop ML Products with good engineering practice and mindset
- Strong desire to solve tough problems with scientific rigour at scale
- An understanding of the value derived from getting results early and iterating
- Education in a quantitative field such as Computer Science, Operations Research, Statistics, Econometrics or Mathematics
- Strong skills in Python and machine learning and deep learning libraries (Pytorch and Tensorflow)
- Passion to answer Product/Engineering questions with data
- Demonstrated use of AI tools (e.g. ChatGPT, Cursor) to develop new or improve workflows, enhance productivity, and drive efficiency at scale
Desired Qualifications
- Subject Matter Expertise in a specific ML domain while maintaining a solid understanding of product and user challenges
- Handle Ambiguity: Navigate and resolve ambiguous problem definitions effectively with or without dedicated Product Manager support
- Metrics Driven: Understand critical business and product metrics, apply the right tools and technologies, and drive efforts to positively influence those metrics
- Experimentation Culture: Foster a fast-paced, high-iteration experimental culture to test and refine solutions quickly
- Collaboration: Work effectively with cross-functional partners and stakeholders to set and achieve optimal outcomes
- Curious: Interest in exploring and learning the latest technologies in the industry
- Utilize Machine Learning: Enhance our products and improve the shopping experience for both users and merchants. This includes leveraging machine learning in areas such as recommendations, personalization, risk, fraud detection, search, and more
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