Job Description
Join the Future at 2026 Labs.
At 2026 Labs, we aren't just building software; we are architecting the digital infrastructure of tomorrow. We are seeking a visionary Senior AI Architect to lead the development of our next-generation predictive intelligence platform. If you are passionate about the convergence of Generative AI, Large Language Models, and scalable cloud architecture, this is your chance to define the standard for the industry.
Why Join Us?
- Work with state-of-the-art technology stack including Python, PyTorch, and Kubernetes.
- Competitive compensation package with equity options.
- Flexible remote-first culture with hubs in San Francisco and New York.
Are you ready to push the boundaries of what's possible in 2026 and beyond?
Responsibilities
- Design and implement scalable, high-performance AI systems capable of processing millions of data points in real-time.
- Lead the architecture and development of our proprietary Large Language Model (LLM) fine-tuning pipelines.
- Collaborate with cross-functional product teams to translate complex business requirements into robust technical solutions.
- Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Ensure system reliability, security, and compliance with industry standards (SOC2, GDPR).
- Conduct code reviews and architecture assessments to maintain code quality and technical debt reduction.
Qualifications
- Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related field (or equivalent practical experience).
- 8+ years of experience in software engineering, with at least 3 years in AI/ML architecture.
- Deep expertise in Python, C++, and modern deep learning frameworks (TensorFlow, PyTorch, JAX).
- Proven experience deploying machine learning models to production using cloud platforms (AWS, GCP, or Azure).
- Strong understanding of MLOps, data pipelines (Airflow, Kafka), and containerization (Docker, Kubernetes).
- Excellent problem-solving skills and ability to communicate complex technical concepts to non-technical stakeholders.