Job Description
We are not merely predicting the future; we are engineering it. At Apex Horizon Technologies, we are building the foundational operating system for the year 2026. We are seeking a visionary Principal AI Architect to lead our research into autonomous agents and multimodal reasoning systems.
In this role, you will bridge the gap between theoretical AI research and production-grade infrastructure. You won't just be maintaining models; you will be defining the protocols for the next generation of intelligent software that operates independently, learns from real-time data streams, and orchestrates complex workflows without human intervention.
Join a team of world-class engineers, researchers, and futurists committed to solving the hardest problems in artificial general intelligence (AGI) infrastructure.
Responsibilities
- Architect Next-Gen Agents: Design and implement self-improving autonomous agent architectures capable of complex multi-step reasoning and tool usage.
- Multimodal Integration: Lead the integration of vision, language, and audio modalities into unified reasoning engines.
- Infrastructure Optimization: Overhaul our inference pipelines to support low-latency, high-throughput deployment of Large Language Models (LLMs).
- R&D Leadership: Spearhead internal research initiatives to pioneer techniques in memory-efficient transformer architectures and reinforcement learning from human feedback (RLHF) at scale.
- Collaborative Engineering: Work closely with product teams to translate cutting-edge AI capabilities into consumer-facing applications.
- Code Review & Mentorship: Establish code quality standards and mentor junior engineers to ensure best practices in AI development.
Qualifications
- Foundational Expertise: 5+ years of experience in machine learning engineering, deep learning, or artificial intelligence research.
- Technical Stack: Proficiency in Python, PyTorch or JAX, and experience with distributed computing frameworks (e.g., Ray, Kubernetes).
- Algorithm Mastery: Deep understanding of transformer models, attention mechanisms, and optimization algorithms.
- System Design: Proven ability to design scalable, fault-tolerant systems for high-volume data processing.
- Education: Master’s degree or PhD in Computer Science, Mathematics, or a related technical field.
- Future-Forward Mindset: Demonstrated ability to identify emerging trends in AI and adapt architectural strategies accordingly.