Job Description
Shape the Future of Intelligence. Zai Future Systems is at the forefront of defining the technological landscape for 2026 and beyond. We are seeking a visionary Senior AI/ML Engineer to lead the development of next-generation artificial intelligence solutions that will redefine industry standards.
In this pivotal role, you will not just implement existing models; you will architect the infrastructure for the future. You will work with a world-class team of data scientists, researchers, and engineers to build scalable, ethical, and high-performance AI systems that solve complex real-world problems.
Why join us?
- Work on cutting-edge projects that define the 2026 tech roadmap.
- Competitive compensation package and equity options.
- Flexible remote-first culture with premium benefits.
If you are passionate about pushing the boundaries of what is possible with Machine Learning and Deep Learning, we want to hear from you.
Responsibilities
- Architect and Design: Design scalable, robust, and secure machine learning architectures capable of processing petabytes of data in real-time.
- Model Development: Lead the end-to-end lifecycle of ML models, from research and prototyping to deployment and monitoring in production environments.
- Optimization: Optimize existing models for speed, accuracy, and resource efficiency using techniques like quantization and pruning.
- MLOps Implementation: Implement and maintain CI/CD pipelines for machine learning, ensuring reproducibility and automation.
- Collaboration: Collaborate with cross-functional teams (Product, Engineering, Data Science) to translate business requirements into technical solutions.
- Research: Stay abreast of the latest advancements in AI research and evaluate their applicability to our product suite.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, Statistics, or a related field.
- Experience: Minimum of 5+ years of professional experience in Machine Learning and Deep Learning.
- Programming: Proficiency in Python, with strong experience in frameworks such as TensorFlow, PyTorch, or JAX.
- Cloud Skills: Hands-on experience with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
- Algorithms: Deep understanding of statistical methods, optimization techniques, and neural network architectures.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.