• python
• AI
• Big Data Ecosystem

Job Description

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 (SFT, RLHF) and application of Large Language Models (LLMs).
• Engineering & Performance Optimization: Collaborate with backend and architecture teams to optimize online inference latency and resource consumption, ensuring high availability and stability under massive concurrent traffic.
• SOTA Tracking: Keep abreast of the latest advancements in AI across academia and industry (State-of-the-Art). Conduct technical research and rapid prototyping to validate new ideas against business needs.

Qualifications

• Education: Master’s degree or above in Computer Science, Mathematics, Statistics, Automation, or a related field.
• Programming Skills: Solid foundation in data structures and algorithms; proficient in Python and highly familiar with C++ or Java; excellent coding habits and engineering practices.
• AI Fundamentals: Strong mathematical background (Linear Algebra, Probability, Optimization); deep understanding of classical machine learning algorithms (LR, Tree-based models like XGBoost/LightGBM) and deep learning architectures (CNN, RNN, Transformer).
• Frameworks: Hands-on proficiency with at least one mainstream deep learning framework, such as PyTorch or TensorFlow.
• Comprehensive Skills: Strong data sensitivity and business acumen, with the ability to abstract complex commercial problems into mathematical/algorithmic models; excellent communication skills and ability to thrive in a fast-paced environment.

💡 Preferred Qualifications

• Academic / Competitions: Publications in top-tier AI conferences/journals (e.g., NeurIPS, ICML, ICLR, KDD, CVPR, ACL) or top-tier ranking/Gold medals in international data mining/programming competitions (e.g., Kaggle, ACM ICPC).
• Big Data Ecosystem: Proficiency with big data processing platforms such as Hadoop, Spark, Hive, or Flink for massive data analysis and feature mining.

High-Performance Deployment: Experience with model compression techniques (quantization, pruning, distillation) and familiarity with high-performance inference and deployment toolchains such as TensorRT, ONNX, or Triton.

If interested, please send cv to lucy.zhang@manpowergrc.hk