Company Introduction
The Fourth Paradigm is a major player in China's intelligent decision-making market, dedicated to rapidly implementing enterprise-level artificial intelligence on a large scale. We provide technologies, products, and solutions centered around "decision-oriented AI" and "generative AI", facilitating the digital transformation of traditional enterprises. Our clientele spans various industries including finance, retail, manufacturing, energy and electricity, telecommunications, and healthcare. At The Fourth Paradigm, we prioritize independent research and application of cutting-edge technologies across various AI fields, contributing to the development of national artificial intelligence technologies and application standards. Our expertise lies in areas such as Automatic Machine Learning (AutoML), Transfer Learning, Automatic Reinforcement Learning, and Environmental Learning. We released our self-developed multimodal large model product, "4Paradigm SageGPT", in February 2023, accumulating dozens of early AIGC industry applications in China. In September 2023, we were listed on the Hong Kong Stock Exchange.
Our Team
The Ministry of Science and Technology is currently focusing on cutting-edge technology research and application implementation in fields such as AI big models, computer vision, natural language processing, machine learning, decision optimization, and speech. Internally, we adopt a more equal and friendly open-source community model, allowing everyone to freely choose tasks according to their interests and wishes. In such an environment, you can have close contact with many different technical fields and business tracks, thereby quickly improving your comprehensive capabilities. We provide a first-class work environment, innovative work models, sufficient computing resources, and competitive compensation and benefits. If you are an outstanding R&D talent passionate about exploring cutting-edge technological developments and transforming advanced scientific research results into practical products, we look forward to your joining!
Base Locations: Beijing/Shanghai/Shenzhen/Wuhan/Singapore
Interview Format
If you are shortlisted, you will undergo the online written test stage, which includes code and algorithm questions. You will be notified of the specific time and arrangement of the written test through email and SMS. After passing the written test, you can enter the second interview stage. The entire interview process consists of about 2-3 rounds. If the interview is approved, the offer can be quickly issued for integration into the job.
Responsibilities:
- Provide optimization methods and solutions for practical problems using leading machine learning, reinforcement learning, or operations research techniques.
- Attempt to design leading machine learning or reinforcement learning algorithms and computing frameworks to improve the execution efficiency of machine learning or reinforcement learning systems.
- Attempt to design leading multi-objective optimization algorithms, non-deterministic optimization algorithms, and online optimization algorithms to improve the efficiency of algorithm optimization.
- Abstract practical problems, design and develop machine learning, reinforcement learning, or operations optimization components to reduce the complexity of solution implementation.
- Continuously improve the usability and ease of use of machine learning, reinforcement learning algorithms, or operations optimization algorithms, reducing the usage threshold.
- Create more valuable machine learning, reinforcement learning, or operations optimization products, driving product improvement or customer business growth through technical innovation.
Requirements:
- Bachelor's degree or above in computer science, mathematics, or related fields from a top university.
- Strong foundation in mathematics, data structures, algorithms, and familiarity with basic Linux operations.
- Some research foundation in machine learning, operations optimization, reinforcement learning, with substantial practical experience in operations optimization, machine learning, and reinforcement learning.
- Good mathematical foundation and solid programming skills, proficient in Python, C++, or another commonly used programming language.
- Deep understanding of distributed computing frameworks.
- Strong business understanding and learning ability, proactive communication skills.
Preferred Qualifications:
- Strong coding skills preferred, with various competition awards (e.g., Kaggle, Tianchi, DF, DC) or participation in ACM programming competitions, or significant impact from open-source projects on GitHub.
- Publication of papers at top conferences or journals such as Interspeech, ICASSP, ACL, EMNLP, NAACL.
- Doctoral research experience and successful practical application experience in machine learning, reinforcement learning, or operations optimization-related fields.
