Job Description
Are you ready to architect the infrastructure of tomorrow? Nexus Horizon Labs is seeking a visionary Future-Proof AI Architect to lead our Research and Development division. As we look toward 2026, we are building systems that don't just predict the future—they create it.
In this high-impact role, you will define the architectural boundaries of next-generation autonomous agents and predictive neural networks. If you are passionate about the convergence of Generative AI, ethics, and scalable infrastructure, this is your opportunity to define the standard for intelligent systems.
Why Join Us?
- Work on projects that will define the technological landscape of 2026.
- Competitive compensation package including equity.
- Flexible remote-first culture with a hub in the heart of San Francisco.
Key Objectives
Our goal is to develop self-evolving algorithms that can operate with minimal human intervention while adhering to strict ethical frameworks. You will be the bridge between theoretical computer science and production-grade deployment.
Responsibilities
- Architect Design: Design and implement scalable, fault-tolerant AI architectures capable of handling exabyte-scale data streams.
- Autonomous Agents: Lead the development of next-generation autonomous agents that leverage multi-modal learning to solve complex, unstructured problems.
- System Optimization: Optimize model inference times and reduce latency in real-time decision-making systems.
- Ethical AI Frameworks: Establish and enforce guidelines for fairness, transparency, and safety in autonomous decision-making processes.
- R&D Leadership: Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate research into product features.
- Trend Analysis: Continuously monitor emerging AI paradigms to ensure our technology remains ahead of the curve through 2026 and beyond.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field (or equivalent extensive industry experience).
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, and distributed computing systems (Kubernetes, Docker).
- Experience: 5+ years of experience in machine learning engineering, with a focus on Large Language Models (LLMs) or Reinforcement Learning.
- System Design: Proven track record of designing complex, high-availability systems at scale.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and leadership.
- Forward-Thinking: A demonstrated history of working on cutting-edge, experimental technologies.