Job Description
We are Zai Corp, a pioneer in futuristic computing, and we are embarking on Project 2026. Our mission is to architect the next generation of autonomous AI ecosystems that will redefine human-machine interaction. We are looking for a visionary Senior AI Engineer to lead the development of our core intelligence infrastructure.
In this role, you won't just be maintaining existing systems; you will be building the foundation for the future. You will work with state-of-the-art Generative AI, Agentic workflows, and next-gen vector databases. If you are obsessed with scalability, ethics in AI, and pushing technical boundaries, we want to hear from you.
Why Join Us?
- Competitive compensation package with equity options.
- Work with cutting-edge technology in a fully remote-first environment.
- Opportunity to shape the roadmap for our flagship 2026 product suite.
Responsibilities
- Architect and optimize high-performance inference engines for large-scale LLM deployments.
- Design and implement autonomous AI agents capable of complex, multi-step reasoning and execution.
- Develop and fine-tune foundation models on proprietary datasets to improve domain-specific accuracy.
- Build robust MLOps pipelines ensuring seamless model training, evaluation, and deployment.
- Collaborate with cross-functional teams to integrate AI capabilities into enterprise-grade software solutions.
- Ensure the ethical, safe, and compliant use of AI technologies.
Qualifications
- Master's degree or PhD in Computer Science, Machine Learning, or a related technical field (or equivalent professional experience).
- 5+ years of professional experience in software engineering with a strong focus on Machine Learning and Deep Learning.
- Expert proficiency in Python, PyTorch, or TensorFlow.
- Proven experience with Large Language Models (LLMs), RAG architectures, and Vector Databases (e.g., Pinecone, Milvus).
- Experience with cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Strong understanding of Natural Language Processing (NLP), Transformer architectures, and prompt engineering.