Python - AI Engineer

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.