Job Description
Are you ready to define the technological landscape of 2026?
Nexus Horizon Labs is seeking a visionary Senior AI Architect to spearhead the development of our next-generation Artificial General Intelligence (AGI) systems. In this pivotal role, you will bridge the gap between theoretical AI research and scalable, production-grade engineering, ensuring our platforms remain at the forefront of the industry.
We are not just building software; we are architecting the future. If you thrive in high-stakes environments and possess a deep understanding of neural architectures, large language models (LLMs), and distributed computing, we want to hear from you.
Why Join Us?
- Work on the frontier of AI development for the year 2026 and beyond.
- Competitive equity package and top-tier compensation.
- Flexible remote-first culture with a vibrant San Francisco hub.
Responsibilities
- Architectural Leadership: Define the high-level technical vision and architecture for our core AGI models, ensuring scalability, robustness, and security.
- System Design: Design and implement complex distributed systems capable of processing petabytes of data in real-time.
- Model Optimization: Oversee the training, fine-tuning, and optimization of large-scale neural networks to improve inference speed and accuracy.
- Technical Mentorship: Lead a team of brilliant engineers and data scientists, fostering a culture of continuous learning and innovation.
- Strategy & Roadmap: Collaborate with product and research teams to translate business objectives into technical roadmaps.
- Risk Management: Identify potential technical risks early and implement mitigation strategies to ensure project delivery.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of experience in software engineering with a strong focus on Machine Learning and Deep Learning.
- Technical Skills: Proficiency in Python, C++, and frameworks such as TensorFlow, PyTorch, or JAX.
- Architecture: Deep expertise in designing scalable microservices and cloud-native applications (AWS, GCP, or Azure).
- Research: Strong background in NLP, Computer Vision, or Reinforcement Learning.
- Soft Skills: Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.