Job Description
Join 2026 Systems and shape the future of Artificial Intelligence.
We are looking for a visionary Lead AI Architect to spearhead our research into next-generation generative models and autonomous agents. As we look toward the 2026 horizon, we are building the infrastructure that will redefine human-computer interaction. If you are passionate about pushing the boundaries of Large Language Models (LLMs) and building scalable, ethical AI systems, this is your opportunity to lead a world-class engineering team.
Why Join Us?
- Impactful Work: Directly contribute to the core architecture powering the AI of tomorrow.
- Top-Tier Team: Collaborate with Ph.D. researchers and senior engineers from leading tech giants.
- Modern Stack: Work with state-of-the-art tools including PyTorch, Kubernetes, and proprietary quantum-enhanced compute stacks.
Located in the heart of San Francisco's tech district, 2026 Systems offers a competitive compensation package and a remote-first culture that values deep work and innovation.
Responsibilities
- Design & Architecture: Architect scalable, fault-tolerant AI systems capable of processing petabytes of data in real-time.
- Model Development: Lead the research and fine-tuning of Large Language Models (LLMs) for specific vertical applications.
- Team Leadership: Mentor a diverse team of data scientists and ML engineers, fostering a culture of technical excellence and continuous learning.
- Strategy: Define the long-term technical roadmap for our AI infrastructure and evaluate emerging technologies (e.g., Neural Architecture Search).
- Collaboration: Partner with product and engineering teams to translate complex AI capabilities into user-friendly products.
- R&D: Push the boundaries of current AI limitations by exploring novel architectures and training methodologies.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 8+ years of experience in software engineering, with at least 5 years specifically in Machine Learning/AI.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and distributed computing systems (e.g., Spark, Kubernetes).
- AI Expertise: Proven track record of working with NLP, Transformers, or Generative AI models.
- Leadership: Demonstrated ability to lead high-performing engineering teams and manage cross-functional projects.
- Problem Solving: Strong analytical skills with a focus on solving complex, unstructured problems.