Job Description
Are you ready to architect the future of intelligence?
Nexus Future Systems is currently recruiting for Project 2026, our groundbreaking initiative to deploy autonomous, sentient-level AI frameworks by the end of the decade. We are looking for a visionary Senior AI Architect to lead the infrastructure and scalability of our next-generation neural networks.
In this role, you won't just write code; you will define the standards of tomorrow. You will work at the intersection of deep learning, high-performance computing, and ethical AI governance. Join us in building the technological foundation for the year 2026 and beyond.
Why Join Project 2026?
- Work on cutting-edge Artificial General Intelligence (AGI) infrastructure.
- Competitive compensation and equity packages.
- Flexible remote-first culture with a hub in San Francisco.
Responsibilities
- System Design: Design and implement scalable AI infrastructure for Project 2026 utilizing PyTorch, TensorFlow, and custom distributed computing frameworks.
- Model Optimization: Optimize large language models (LLMs) and neural networks for real-time, high-throughput environments, ensuring zero-latency processing.
- Integration: Collaborate with hardware engineers to integrate AI solutions directly into next-gen consumer hardware and cloud ecosystems.
- Ethical AI: Establish and enforce governance frameworks to ensure algorithmic outputs are fair, unbiased, and compliant with international safety standards.
- Mentorship: Lead a team of junior data scientists and engineers, providing technical mentorship and fostering a culture of innovation.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Artificial Intelligence, Robotics, or a related technical field.
- Experience: 5+ years of professional experience in deploying machine learning models at scale, with at least 2 years in a leadership or architect role.
- Technical Stack: Proficiency in Python, C++, and distributed computing systems (Kubernetes, Docker, Apache Spark).
- Domain Knowledge: Deep understanding of Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Communication: Exceptional ability to translate complex technical concepts into clear, actionable strategies for stakeholders.