Job Description
The Future is Now. Nexus Horizon Labs is pioneering the next generation of sentient computing. We are looking for a visionary Senior AI & Autonomous Systems Architect to lead our R&D division into the uncharted territories of 2026.
In this pivotal role, you will be responsible for architecting the neural frameworks that power our autonomous agents and next-gen user interfaces. We are not just building software; we are defining the ethical and technical boundaries of Artificial General Intelligence (AGI). If you have a passion for pushing the limits of what machines can learn and do, this is your opportunity to shape the technological landscape of the future.
Why Nexus Horizon?
- Work on cutting-edge projects that redefine human-machine interaction.
- Competitive equity package and performance bonuses.
- Flexible remote-first policy with access to state-of-the-art research facilities in SF.
- Opportunity to mentor the next generation of AI researchers.
Responsibilities
- System Architecture: Design scalable, fault-tolerant neural network architectures capable of handling billions of data points in real-time.
- R&D Leadership: Lead a cross-functional team in researching and implementing advanced Reinforcement Learning (RL) and Deep Learning models.
- Quantum Integration: Collaborate with quantum computing researchers to hybridize classical AI models with quantum algorithms for exponential speed-ups.
- Optimization: Optimize model inference latency and resource utilization for deployment on edge devices and distributed cloud environments.
- AI Ethics & Governance: Establish rigorous guidelines for algorithmic bias, transparency, and the safe deployment of autonomous decision-making systems.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, Robotics, or a related technical field.
- Experience: 8+ years of experience in software engineering and machine learning architecture, with a focus on Large Language Models (LLMs) or Autonomous Systems.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, and CUDA; experience with Kubernetes and AWS/Azure/GCP.
- Core Competencies: Strong understanding of Neural Architecture Search (NAS), Federated Learning, and Natural Language Processing (NLP).
- Soft Skills: Exceptional communication skills with the ability to translate complex technical concepts to non-technical stakeholders.