Job Description
We are pioneering the Project 2026 initiative, a groundbreaking research effort to redefine the boundaries of artificial general intelligence and autonomous systems. We are seeking a visionary Senior AI Architect to lead the architectural design and implementation of our next-generation neural frameworks.
In this role, you will be at the forefront of technological evolution, designing scalable, robust, and secure AI systems that will power the digital infrastructure of tomorrow. You will work closely with cross-functional teams of data scientists, engineers, and product managers to deliver cutting-edge solutions that push the industry forward.
Why join Project 2026?
- Impactful Work: Build the foundational architecture for the future of AI.
- Top-Tier Compensation: Competitive salary and equity packages.
- Global Collaboration: Work with elite talent from around the world.
Responsibilities
- Lead Architecture Design: Define the high-level architecture for complex AI systems, ensuring scalability, performance, and security.
- R&D Leadership: Spearhead research into novel algorithms and machine learning paradigms specific to the 2026 roadmap.
- Model Optimization: Oversee the optimization of large language models and neural networks for real-time inference and edge deployment.
- Technical Strategy: Translate business requirements into robust technical solutions and guide the engineering team in best practices.
- System Integration: Integrate AI components into broader cloud ecosystems and legacy systems seamlessly.
- Mentorship: Mentor junior architects and data scientists, fostering a culture of technical excellence and innovation.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field, with a focus on Artificial Intelligence or Machine Learning.
- Experience: 7+ years of experience in software engineering, with at least 4 years specifically focused on AI/ML architecture.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and modern Deep Learning frameworks.
- Domain Knowledge: Proven track record of implementing Large Language Models (LLMs) and generative AI solutions.
- System Design: Strong understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and MLOps pipelines.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.