Job Description
We are building the foundation for the next era of intelligence.
At Apex Future Systems, we don't just predict the future; we engineer it. We are seeking a visionary Lead AI Architect to spearhead Project 2026, our flagship initiative to develop next-generation autonomous reasoning systems capable of reshaping global industries.
In this pivotal role, you will design the neural infrastructure for systems that learn, adapt, and evolve. You will work at the intersection of theoretical research and scalable engineering, ensuring our platforms are not only powerful but also ethically grounded and future-proof.
Join us in defining the trajectory of artificial general intelligence and leave a legacy that spans decades.
At Apex Future Systems, we don't just predict the future; we engineer it. We are seeking a visionary Lead AI Architect to spearhead Project 2026, our flagship initiative to develop next-generation autonomous reasoning systems capable of reshaping global industries.
In this pivotal role, you will design the neural infrastructure for systems that learn, adapt, and evolve. You will work at the intersection of theoretical research and scalable engineering, ensuring our platforms are not only powerful but also ethically grounded and future-proof.
Join us in defining the trajectory of artificial general intelligence and leave a legacy that spans decades.
Responsibilities
- Design and architect scalable, high-performance AI systems for Project 2026.
- Lead research initiatives into large language models and transformer architectures.
- Collaborate with cross-functional teams including data scientists, ethicists, and software engineers.
- Optimize model inference latency and accuracy in production environments.
- Define technical roadmaps and mentor junior engineers on best practices in AI engineering.
- Ensure compliance with data privacy and safety standards in all model deployments.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related technical field.
- 5+ years of professional experience in Machine Learning, Deep Learning, or AI research.
- Expert proficiency in Python, PyTorch, TensorFlow, and CUDA.
- Strong experience with cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Proven track record of deploying state-of-the-art models to production.
- Experience with MLOps pipelines and model versioning tools.