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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