Job Description
Join the Vanguard of the Year 2026
At Year 2026 Labs, we are not just predicting the future; we are engineering it. We are a cutting-edge research and development firm dedicated to solving humanity's most complex challenges through advanced Artificial Intelligence and Quantum Computing. We are seeking a visionary Lead AI Architect to spearhead our next generation of autonomous systems.
In this pivotal role, you will bridge the gap between theoretical machine learning breakthroughs and scalable, production-grade software. You will be responsible for defining the architectural framework that powers our vision for the year 2026 and beyond.
Why Year 2026 Labs?
- Impactful Work: Your algorithms will directly influence global infrastructure and smart city integration.
- Top-Tier Talent: Collaborate with the brightest minds in Silicon Valley and beyond.
- Equity & Compensation: Competitive base salary plus significant equity stake in a unicorn startup.
Are you ready to define the future? Apply today.
Responsibilities
- Architect and lead the development of next-generation neural networks and generative AI models.
- Define technical strategies and roadmaps for AI initiatives that align with the 2026 corporate vision.
- Oversee the end-to-end machine learning lifecycle, from data ingestion and feature engineering to model deployment and monitoring.
- Ensure system scalability, security, and fault tolerance in high-traffic environments.
- Collaborate with product managers and engineers to translate complex business requirements into technical specifications.
- Conduct deep-dive research into emerging technologies to keep the 2026 roadmap ahead of the curve.
Qualifications
- Master’s degree or PhD in Computer Science, Mathematics, or a related technical field.
- 10+ years of professional experience in software engineering, with at least 5 years specifically in AI/ML architecture.
- Extensive experience with Python, PyTorch, TensorFlow, and distributed computing frameworks.
- Proven track record of deploying large-scale ML models in cloud environments (AWS, GCP, or Azure).
- Strong understanding of NLP, Computer Vision, or Reinforcement Learning.
- Demonstrated leadership experience in managing technical teams and cross-functional projects.