PERSOL APAC Hiring! Full Time Machine Learning Engineer (Recommendation - Search) in - Ricebowl

About the company:

We have partnered with a renowned global leader in information and communications technology (ICT) infrastructure and smart devices. They are providing full-stack, all-scenario solution for products and services carriers, enterprises, governments, and individual consumers worldwide.

Our client is looking for a Machine Learning Engineer (Recommendation & Search) to join the team.

Role Overview:

We are seeking a Machine Learning Engineer to build and scale our large-scale content/ads recommendation and search systems. You will bridge the gap between Big Data engineering and ML algorithms, responsible for everything from building high-performance data pipelines (Spark/Hive) to optimizing state-of-the-art ML models (TensorFlow/PyTorch) for production.

Responsibilities:

• Develop and optimize recommendation/search algorithms (CTR, CVR, Multitask models, Retrieval & Ranking).
• Design scalable ETL pipelines and data models to process structured/unstructured data using Spark, Hive, and Hadoop.
• Own the entire ML lifecycle. Optimize complex code for "Cost, Compute, and Storage" efficiency across offline training and online inference.
• Launch A/B experiments and continuously optimize models to drive key business metrics and performance indicators.
• Maintain data quality, accuracy, and compliance with company data privacy and security policies.
• Create data visualizations and reports (Tableau/PowerBI) to communicate system insights to cross-functional teams.

Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
• Proficient in languages such as Python, Java, or Scala, with deep expertise in coding, data structures, algorithms, and handling multi-dimensional arrays/tensors.
• Proven experience in building full stack recommender systems, including collaborative filtering, CTR, CVR, CTCVR, and multitask models. (And/Or) Experience in building full stack search systems, including user query understanding, retrieval and ranking.
• Strong production experience with Apache Spark, Hive, Hadoop, and Linux. Exceptional capability in writing highly optimized, complex SQL/Hive queries for massive datasets.
• Hands-on experience with scalable model development using TensorFlow, PyTorch, or similar frameworks, including custom operators, layers, losses, and optimizers.
• Skilled in distributed training (GPU/TPU) and deploying large models with sparse features. Proficient in writing optimized, complex SQL/Hive queries.
• Ability to identify and resolve performance bottlenecks across the entire data-to-model pipeline.

Interested candidates, who wish to apply for the advertised position, please click on "Apply Now". We regret that only shortlisted candidates will be notified.

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