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Senior AI Engineer at Repkon

, , -

Full Time

Start Date

Immediate

Expiry Date

27 Jun, 26

Salary

0.0

Posted On

29 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, AI, ML, NumPy, Pandas, Scikit-learn, LLM Framework, LLM APIs, Vector Databases, RAG Architectures, Cloud AI Platform, Version Control, Testing, CI/CD, Docker, Kubernetes

Industry

Internet Marketplace Platforms

Description

Responsibilities: Translate business requirements and algorithmic models into high-quality, production-ready code. Design, develop, test, deploy, and maintain efficient and reliable AI models and systems. Monitor system performance, optimise efficiency, and handle incident troubleshooting to ensure service reliability. Safeguard production AI systems in terms of stability, scalability, and security. Collaborate with data scientists, software engineers, and product managers to drive smooth project delivery. Produce clear technical documentation, including architecture designs, API specifications, and operation guides. Contribute to technical decision-making and introduce AI engineering best practices and tools. Perform code reviews and mentor junior engineers. Requirements: Bachelor’s degree or above in Computer Science, AI, ML, Statistics, or related field. 3+ years software development, including 1+ year on Python-based AI projects. Strong Python and AI libraries (e.g. NumPy, Pandas, Scikit-learn). Experience with at least one LLM framework and major LLM APIs. Knowledge of vector databases and RAG architectures. Cloud AI platform experience preferred. Familiar with version control, testing, and CI/CD. Experience deploying AI to production (e.g. Docker, Kubernetes, FastAPI, Flask) is a plus. Experience with large datasets and SQL databases. Fluent Chinese and English; strong communication and learning agility.

Responsibilities

The role involves translating business needs and models into production-ready code, designing, developing, testing, deploying, and maintaining reliable AI systems. Responsibilities also include monitoring performance, ensuring system security, and collaborating with cross-functional teams for project delivery.