Job Description
Shape the Future of Intelligence
Are you ready to architect the systems that will define the next decade? Apex Horizon Technologies is seeking a visionary Lead Architect: Future-Ready AI Infrastructure to join our elite team in San Francisco. We are building the foundational layers of next-generation neural networks and autonomous systems designed for the year 2026 and beyond.
In this high-impact role, you will bridge the gap between theoretical AI breakthroughs and scalable production systems. You won't just be maintaining legacy code; you will be defining the protocols for a new era of machine intelligence.
Why Join Us?
- Work on projects that have a global impact on healthcare, finance, and transportation.
- Access to cutting-edge quantum computing resources and GPU clusters.
- Competitive equity package and top-tier healthcare benefits.
- A culture that prioritizes innovation over bureaucracy.
What You'll Do
Responsibilities
- System Architecture: Design and oversee the deployment of scalable, fault-tolerant AI infrastructure capable of handling petabyte-scale data streams.
- Model Optimization: Lead the optimization of large language models (LLMs) and transformer architectures for edge computing environments.
- R&D Leadership: Collaborate with research scientists to translate academic breakthroughs into practical, deployable software solutions.
- Code Governance: Establish and enforce rigorous coding standards, CI/CD pipelines, and architectural guidelines for the engineering team.
- Future-Proofing: Proactively identify emerging technologies (such as neuromorphic computing) and integrate them into our core technology stack.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related technical field.
- Experience: 8+ years of experience in software engineering, with at least 3 years in a lead or architect role within the AI/ML space.
- Technical Skills: Deep expertise in Python, C++, and distributed systems (Kubernetes, Docker).
- AI Expertise: Proven track record in training, fine-tuning, and deploying generative AI models.
- Problem Solving: Ability to deconstruct complex problems into modular, solvable components.