Job Description
Are you ready to architect the future of intelligence? Zai Innovations is seeking a visionary Senior AI/ML Engineer to lead our 2026 roadmap. We are building the next generation of autonomous systems, and we need a technical expert who thrives on complexity and innovation.
In this role, you won't just maintain existing models; you will pioneer new architectures that define the technological landscape of the coming decade. You will work at the intersection of research and production, ensuring our AI solutions are scalable, ethical, and transformative.
Why Join Us?
At Zai Innovations, we are not just keeping up with the future; we are defining it. You will have the autonomy to experiment with cutting-edge technologies, mentor a world-class engineering team, and impact millions of users globally.
Responsibilities
- Lead Model Development: Design, train, and deploy state-of-the-art machine learning and deep learning models tailored for 2026 scalability.
- Architectural Strategy: Define the technical strategy for AI infrastructure, focusing on robust, low-latency systems.
- Performance Optimization: Improve model inference speeds and accuracy through rigorous testing, quantization, and pruning techniques.
- MLOps Implementation: Establish CI/CD pipelines, automated monitoring systems, and model governance frameworks.
- Collaboration: Partner with product managers and engineering teams to translate complex business requirements into technical solutions.
- R&D: Stay ahead of the curve by researching emerging AI trends, LLMs, and generative AI architectures.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field (PhD preferred).
- Experience: 5+ years of professional experience in Machine Learning Engineering or Data Science.
- Programming: Expert proficiency in Python and frameworks such as PyTorch, TensorFlow, or JAX.
- Cloud: Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Tools: Experience with MLOps tools (MLflow, Kubeflow) and version control (Git).
- Problem Solving: Ability to solve complex, unstructured problems and debug high-stakes production issues.