Job Description
Are you ready to define the future of technology?
Nebula Innovations is seeking a visionary Senior AI Architect to lead our engineering division into the 2026 era. We are not just building software; we are architecting the cognitive infrastructure for the next decade. In this role, you will be responsible for designing scalable, high-performance AI systems that integrate Generative AI, Quantum-ready algorithms, and advanced Machine Learning pipelines.
The 2026 Vision:
We are looking for a technical leader who can bridge the gap between theoretical breakthroughs and production-grade reality. You will guide a team of elite engineers in deploying Large Language Models (LLMs) and autonomous agents that will power the next generation of enterprise solutions.
Why This Role?
- Impactful Work: Directly influence the roadmap that defines the tech landscape of 2026.
- Top-Tier Compensation: Competitive base salary plus equity package.
- Flexible Environment: Hybrid work model based in the heart of San Francisco.
Apply today to shape the future.
Responsibilities
- Architect Next-Gen Systems: Design and implement scalable AI infrastructure capable of handling petabyte-scale data and real-time inference.
- Lead Technical Strategy: Define the technical vision for our 2026 roadmap, focusing on Agentic AI and Edge Computing integration.
- MLOps Excellence: Build and maintain robust MLOps pipelines (CI/CD, model registry, monitoring) to ensure model reliability and performance.
- Team Leadership: Mentor senior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Cross-Functional Collaboration: Partner with product managers and stakeholders to translate complex AI capabilities into business value.
- R&D Initiatives: Stay at the forefront of AI trends, researching new methodologies like Federated Learning or Neuromorphic Computing.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 8+ years of software engineering experience with a focus on Machine Learning and Deep Learning.
- Tech Stack: Expert proficiency in Python, PyTorch, TensorFlow, and CUDA.
- System Design: Deep understanding of distributed systems, microservices architecture, and cloud platforms (AWS, GCP, or Azure).
- AI Specialization: Proven track record of deploying LLMs (e.g., GPT, LLaMA) and RAG architectures in production environments.
- Soft Skills: Exceptional communication skills with the ability to explain complex technical concepts to non-technical stakeholders.