of key techniques including Pre-training (PT), Continuous Pre-training (CPT), Supervised Fine-Tuning (SFT), Reinforcement Learning (RL), and AI Agents.
3. Possess an application-oriented mindset, collaborate with business teams to realize the value of algorithms, and continuously explore new opportunities to enhance operational efficiency and manpower productivity.
Qualifications
Minimum Qualifications
- Bachelor's degree or higher in Computer Science, Mathematics, Artificial Intelligence, or related fields. Solid foundational knowledge of machine learning and hands-on experience with algorithms in real-world business scenarios are required.
- Expert in the practical application of large models in the industry, with proven experience in SFT, RL, and Agents. Familiarity with training frameworks like LLaMA Factory is essential.
- Proficient in Python and deep learning frameworks such as PyTorch or TensorFlow. Strong problem-solving skills are a must.
- Strong sense of responsibility and a commitment to continuous learning, with the ability to stay abreast of cutting-edge large model technologies and apply them to business problems.
Preferred Qualifications
- Published work in top-tier conferences (KDD, NeurIPS, ICML, SIGIR, WSDM, WWW, AAAI, IJCAI, RecSys, etc.) or success in ML competitions.
- Passion for building agentic systems that drive real-world business outcomes.