Job Description
Shape the Future of Intelligence. Apex Horizon Systems is at the forefront of the 2026 AI revolution. We are seeking a visionary Lead AI Architect to design the next generation of adaptive neural networks and autonomous systems.
In this pivotal role, you will bridge the gap between theoretical research and scalable production systems. You will define the architectural standards for our proprietary Large Language Models (LLMs) and ensure our infrastructure is ready for the exponential growth predicted for 2026 and beyond.
Join a team of elite engineers and data scientists pushing the boundaries of what is possible. If you are passionate about the future of AI and want to build systems that redefine human-machine interaction, we want to hear from you.
Responsibilities
- Architectural Design: Lead the end-to-end design of AI infrastructure, focusing on scalability, fault tolerance, and low-latency processing.
- Model Development: Oversee the research and implementation of state-of-the-art machine learning models, specifically targeting 2026 benchmarks in generative AI and reasoning.
- Team Leadership: Mentor a high-performing team of ML engineers and data scientists, fostering a culture of innovation and technical excellence.
- Strategic Vision: Collaborate with C-suite executives to align AI capabilities with long-term business goals and product roadmaps.
- Optimization: Drive performance optimization strategies to reduce inference costs and improve model efficiency.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related field.
- Experience: 7+ years of experience in software engineering and machine learning, with at least 3 years in a leadership or architectural role.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and distributed computing frameworks (e.g., Kubernetes, Ray).
- Domain Knowledge: Strong understanding of NLP, Computer Vision, or Reinforcement Learning.
- Problem Solving: Proven track record of solving complex, ambiguous problems in high-stakes environments.