Description and Requirements

Key Responsibilities

Design, develop, and maintain backend services for Sales IT systems using Java and Spring Framework/Spring Boot.
Build and support microservices (REST APIs, integration patterns, service reliability/observability basics).
Develop AI/ML-related code in Python, including data preparation, training experimentation, and evaluation.
Participate in AI projects with hands-on model training experience (e.g., feature engineering or embeddings, training runs, metrics, iteration, reproducibility).
Integrate trained models into applications (online inference APIs or batch jobs), ensuring performance, stability, and maintainability.
Work with relational databases and SQL collaborate on data modeling and query/performance considerations.
Use modern engineering practices and tools (Git, code reviews, testing, CI/CD) to deliver production-quality software.
Partner with stakeholders to clarify business needs, translate them into technical solutions, and iterate based on feedback.
Demonstrate ownership: break down ambiguous problems, propose options, and drive tasks to completion with minimal supervision.
Required Qualifications
Bachelor's degree in Computer Science or a related field (or equivalent experience).
Graduates from top-tier universities or those holding a Master's degree are preferred.
Solid programming skills in Java and Python.
Familiarity with Spring Framework (Spring Boot preferred).
Understanding of microservices architecture and API development.
Hands-on experience with at least one ML/DL framework, e.g. PyTorch, TensorFlow, or scikit-learn.
Real project experience in AI training (internship, academic, or industry), including training and evaluation of models.
Working knowledge of relational databases (e.g., PostgreSQL/MySQL/Oracle) and SQL.
Proficiency with common development tools and workflows (Git, debugging, build tools, testing).
Strong self-motivation and collaboration skills.
Preferred Qualifications (Nice to Have)
Experience deploying AI models to production (batch/streaming/online inference) and basic MLOps concepts.
Familiarity with containers and cloud (Docker/Kubernetes AWS/Azure/GCP).
Experience with distributed systems, messaging, or caching (Kafka/RabbitMQ/Redis, etc.).
Ability to speak Chinese (Mandarin) is a plus.
What We're Looking For (Behavioral / Mindset)
Ownership & self-directed execution: able to work independently, manage priorities, and communicate progress/risks clearly.
Product mindset: understands why behind requirements, cares about user/business impact, and can propose improvements instead of only implementing tickets.
Ideas & curiosity: brings viewpoints, experiments responsibly, and continuously learns new AI and engineering practices.
Team collaboration: works effectively in a global team and contributes to a healthy engineering culture.

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