Job Description
We are at the forefront of defining the technological landscape for 2026 and beyond. Nexus Horizon Labs is seeking a visionary Lead AI Architect to spearhead the development of next-generation generative models and autonomous agent systems. If you are passionate about building the future of intelligence and have a deep technical foundation in machine learning, we want to hear from you.
In this role, you will not just implement existing solutions; you will architect the foundational infrastructure for the AI systems that will define the next decade. You will work with a world-class team of researchers and engineers to push the boundaries of what is possible with Large Language Models (LLMs), multi-modal AI, and agentic workflows.
Why Join Us?
- Shape the Future: Directly influence the roadmap for 2026 AI technologies.
- High Impact: Your work will power applications used by millions globally.
- Top-Tier Compensation: Competitive salary, equity, and benefits.
Responsibilities
- Architect Next-Gen AI Systems: Design and implement scalable, secure, and high-performance generative AI pipelines and LLM orchestration frameworks.
- Model Optimization: Lead initiatives in model fine-tuning, quantization, and efficient inference to deploy models on edge devices and cloud environments.
- Research & Innovation: Stay ahead of the curve on emerging AI trends, evaluating new research papers and methodologies to integrate into our production stack.
- Technical Leadership: Mentor a team of senior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
- System Design: Define the architectural patterns for data ingestion, processing, and model serving at scale.
- Stakeholder Collaboration: Translate complex technical concepts into clear strategies for product and engineering leadership.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field (PhD preferred).
- Experience: 8+ years of professional experience in software engineering, with at least 4 years specifically focused on AI/ML and deep learning architectures.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX. Deep experience with Hugging Face, LangChain, or similar LLM frameworks.
- Cloud Native: Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Mathematical Maturity: Solid foundation in linear algebra, calculus, probability, and statistics.
- Leadership: Proven track record of leading technical teams and delivering complex systems from conception to production.