Job Description
Are you ready to architect the future of intelligence?
At Zai FutureTech, we are building the operating system for the next generation of digital interaction. We are seeking a visionary Senior AI & Machine Learning Engineer to lead the development of next-generation Generative AI models and autonomous agents. If you thrive in a fast-paced, high-impact environment and want to push the boundaries of what is possible with LLMs and Neural Networks, we want to meet you.
As a key member of our elite R&D division, you will not just build models; you will define the architecture that powers the global economy of 2026 and beyond. You will work directly with our CTO and top-tier researchers to deploy scalable, robust, and ethical AI solutions that solve complex real-world problems.
Why Join Us?
- Cutting-Edge Stack: Work with the latest in PyTorch, TensorFlow, and Rust-based inference engines.
- Global Impact: Your work will be integrated into products used by millions worldwide.
- Top-Tier Compensation: Competitive salary, equity package, and comprehensive benefits.
- Flexible Culture: Remote-first hybrid model with a focus on autonomy and results.
Responsibilities
- Model Architecture & Development: Design, train, and optimize large-scale machine learning models, specifically focusing on Generative AI and Natural Language Processing (NLP) pipelines.
- Infrastructure Scaling: Lead the deployment of models to high-performance cloud environments (AWS/Azure) utilizing Kubernetes and containerization technologies for optimal inference speed.
- Research & Innovation: Conduct in-depth research into novel algorithms to improve model accuracy, reduce latency, and minimize hallucination rates in LLM outputs.
- Collaboration: Partner with cross-functional teams including Product Managers, Data Scientists, and Software Engineers to translate business requirements into technical AI solutions.
- MLOps Implementation: Establish robust CI/CD pipelines for machine learning, ensuring reproducibility and seamless model versioning.
- RAG Systems: Engineer advanced Retrieval-Augmented Generation (RAG) systems to enhance the accuracy and context-awareness of AI agents.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Mathematics, Statistics, or a related quantitative field.
- Experience: 5+ years of professional experience in Machine Learning, AI Engineering, or Data Science roles.
- Programming: Expert proficiency in Python (PyTorch, TensorFlow, Scikit-learn) and strong experience with SQL and NoSQL databases.
- Infrastructure: Deep understanding of cloud computing platforms (AWS, GCP) and MLOps practices (Docker, Kubernetes, MLflow, Airflow).
- Communication: Excellent written and verbal communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Problem Solving: Demonstrated track record of solving ambiguous problems and delivering scalable solutions under tight deadlines.