We are seeking an outstanding AI Algorithm Engineer to join our core technical team. In this role, you will dive deep into core business scenarios, leveraging cutting‑edge machine learning and deep learning technologies to extract value from massive datasets. You must possess not only a solid theoretical foundation in algorithms but also exceptional engineering capabilities to translate advanced AI technologies into real business growth and product competitive advantages.
Responsibilities
Model Development & Iteration: Design, train, fine‑tune, and iterate machine learning/deep learning models. Provide industry‑leading algorithmic solutions tailored to solve complex business pain points.
End-to-End Algorithm Lifecycle: Take ownership of the full algorithm pipeline, from data cleaning and feature engineering to model training, online evaluation (A/B testing), and final deployment.
Core Domain Expertise (Select 1-2 based on your team's focus):
Recommendation / Ads / Search: Develop high‑concurrency, low‑latency CTR/CVR prediction models (e.g., DeepFM, DIN, Multi-task learning) and optimize recall and ranking mechanisms.
Computer Vision (CV): Research and develop algorithms for image classification, object detection, image segmentation, facial recognition, or multimodal generation (AIGC).
Natural Language Processing (NLP): Develop algorithms for text classification, sentiment analysis, and information extraction, or lead the fine‑tuning of large language models (LLMs).
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Responsibilities
Model Development & Iteration: Design, train, fine‑tune, and iterate machine learning/deep learning models. Provide industry‑leading algorithmic solutions tailored to solve complex business pain points.
End-to-End Algorithm Lifecycle: Take ownership of the full algorithm pipeline, from data cleaning and feature engineering to model training, online evaluation (A/B testing), and final deployment.
Core Domain Expertise (Select 1-2 based on your team's focus):
Recommendation / Ads / Search: Develop high‑concurrency, low‑latency CTR/CVR prediction models (e.g., DeepFM, DIN, Multi-task learning) and optimize recall and ranking mechanisms.
Computer Vision (CV): Research and develop algorithms for image classification, object detection, image segmentation, facial recognition, or multimodal generation (AIGC).
Natural Language Processing (NLP): Develop algorithms for text classification, sentiment analysis, and information extraction, or lead the fine‑tuning of large language models (LLMs).
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