Job Description
We are on the cusp of a technological revolution. At Apex Future Systems, we are building the foundational architecture for our Project 2026, a next-generation initiative aimed at redefining human-computer interaction through advanced neural networks and quantum computing principles. We are looking for a visionary and technical Senior AI Architect to lead our R&D division in San Francisco.
As part of Project 2026, you will not just be writing code; you will be defining the future. You will bridge the gap between theoretical breakthroughs and scalable production environments. If you are passionate about the intersection of artificial intelligence, deep learning, and long-term strategic planning, this is your opportunity to leave a lasting legacy in the tech industry.
As part of Project 2026, you will not just be writing code; you will be defining the future. You will bridge the gap between theoretical breakthroughs and scalable production environments. If you are passionate about the intersection of artificial intelligence, deep learning, and long-term strategic planning, this is your opportunity to leave a lasting legacy in the tech industry.
Responsibilities
- Architect and design scalable, high-performance AI models for the Project 2026 roadmap.
- Lead a team of machine learning engineers and data scientists in research and development activities.
- Optimize algorithms for speed, accuracy, and energy efficiency in edge computing environments.
- Collaborate with cross-functional teams, including product management and UX design, to translate business requirements into technical solutions.
- Define technical standards and best practices for AI implementation across the organization.
- Stay ahead of industry trends in generative AI and quantum computing to drive innovation.
Qualifications
- Master’s or Ph.D. in Computer Science, Mathematics, or a related field.
- Minimum of 8+ years of experience in software engineering and machine learning.
- Proven expertise in Python, PyTorch, TensorFlow, and distributed systems.
- Experience with large language models (LLMs) and transformer architectures.
- Strong understanding of cloud infrastructure (AWS, GCP, or Azure).
- Excellent leadership and communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.