Job Description
About 2026 Labs
We are pioneering the next generation of cognitive computing, aiming to achieve a paradigm shift in artificial general intelligence by the year 2026. Our mission is to build systems that don't just process data but understand context, nuance, and intent on a human level. We are looking for a Lead AI Architect who shares our vision for a future where technology seamlessly integrates into the fabric of society.
The Role
You will be at the helm of our architectural strategy, bridging the gap between theoretical AI research and scalable, production-grade engineering. You will define the technical roadmap that ensures our 2026 release is not only successful but revolutionary.
Responsibilities
- Architectural Leadership: Design and oversee the implementation of a robust, scalable AI infrastructure capable of supporting millions of concurrent neural interactions.
- Research Integration: Translate cutting-edge academic research into practical, deployable code, specifically focusing on next-gen LLM optimization and reinforcement learning.
- Team Mentorship: Cultivate a culture of technical excellence, mentoring senior engineers and fostering an environment of continuous learning and innovation.
- Roadmap Strategy: Collaborate with the C-suite to define technical milestones for the 2026 product launch, ensuring feasibility and competitive advantage.
- Performance Optimization: Drive initiatives to reduce inference latency and improve model accuracy, ensuring real-time responsiveness in critical applications.
- Cross-Functional Collaboration: Partner with product, security, and design teams to ensure AI solutions align with user needs and compliance standards.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related technical field from a top-tier institution.
- Experience: 8+ years of professional experience in AI/ML engineering, with at least 3 years in a senior or lead architectural role.
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, and distributed systems (Kubernetes, Docker).
- Model Engineering: Proven track record of designing and deploying large-scale transformer models and generative AI systems.
- System Design: Strong understanding of cloud architecture (AWS/Azure/GCP) and high-availability system design.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and drive consensus.