Job Description
About Nexus Future Systems:
We are pioneering the next generation of artificial intelligence, and we are looking for a visionary leader to drive our flagship initiative, Project 2026. Project 2026 is our ambitious roadmap to deploy a self-evolving, quantum-ready AI infrastructure designed to solve complex global challenges by the target year of 2026. We are seeking a Senior AI Architect who is not just proficient in current technologies, but who can architect the systems of tomorrow.
Why Join Us?
- Work on cutting-edge generative AI models.
- Competitive compensation package and equity options.
- Flexible remote-first culture with state-of-the-art offices in SF.
- Opportunity to define the roadmap for the future of AI.
Responsibilities
- Lead Architecture: Design and oversee the end-to-end architecture for Project 2026, ensuring scalability, security, and high performance.
- Model Development: Spearhead the development of proprietary Large Language Models (LLMs) and reinforcement learning agents.
- Technical Strategy: Translate business requirements into technical blueprints and guide the engineering team in implementation.
- Optimization: Optimize existing neural networks for edge computing environments and massive data throughput.
- R&D Leadership: Stay at the forefront of AI research (e.g., Transformers, Diffusion Models) and integrate cutting-edge findings into our pipeline.
- Collaboration: Partner with product managers, data scientists, and security experts to deliver robust AI solutions.
Qualifications
- Experience: 7+ years of experience in software engineering, with at least 4 years specifically in AI/ML architecture.
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (Apache Spark, Kubernetes).
- Domain Knowledge: Deep understanding of Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Cloud Expertise: Hands-on experience deploying models on AWS, Azure, or Google Cloud Platform.
- Soft Skills: Exceptional problem-solving abilities, leadership skills, and the ability to communicate complex technical concepts to non-technical stakeholders.