Job Description:
- Research and development of Petal Ads recommendation algorithms, launch experiments, and continuously optimize the algorithms based on KPI data.
- Collaborate with product and operation strategies to improve click & conversion revenue through algorithm/feature optimization.
- Provide guidance for improving business and user experience indicators.
Skills / Qualifications:
- Master Degree or PhD in Computer Science or other related fields with coding and development background. (In exceptional case, for BS Degree with >5 years of experience in deploying deep-learning algorithms, working with GPU and Tensorflow)
- Has experience in building recommender systems at scale in production using the Tensorflow stack for deep-learning model development and deployment.
- Experience in Recommender systems, Collaborative Models, ctr, cvr, ctcvr multitask models.
- Has experience in training and launching large models with sparse features. Understanding the recommendation metrics, improving them and identify the issues associated with model training and optimization.
- Familiar with Identifying, Profiling, and understanding bottlenecks and performance issues at every stage of the recommendations pipeline in GPU-based RecSys workflows.
- Familiar with CTR estimation algorithms and prediction sorting algorithms commonly used in recommendation systems and have experience in project implementation (or practice).
- Familiar with large-scale distributed machine learning computing theory.
- Has experience in recommendation tools and accelerating ETL, identify the objectives and create new labels through Hive, Scala or similar programming tools.
- Has experience in big data technologies such as Apache Spark, Hive, Scala, Hadoop and Linux.
- Familiar with the Internet operation mode and able to combine operation strategies and algorithms effectively.
- Familiar in development trend of recommendation algorithm research in the industry.
Interested candidate who wish to apply for this position, please click on APPLY NOW
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EA Registration No.: R23117518 | Heah Sian Wei
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