Job Description
Welcome to the future of technology. Nebula Future Systems is pioneering the next generation of intelligent infrastructure. We are looking for a visionary Senior AI Architect (2026 Vision) to lead our research into Artificial General Intelligence (AGI) and scalable machine learning systems. If you are passionate about building the foundational technology that will define the next decade, we want to hear from you.
As a Senior AI Architect, you will not just write code; you will architect the future. You will work on cutting-edge projects involving Large Language Models (LLMs), neural architectures, and quantum-ready AI systems. Join us in shaping the landscape of 2026 and beyond.
Why join Nebula Future Systems?
- Work on projects that define the future of humanity.
- Competitive compensation and equity packages.
- Flexible remote-first culture with premium benefits.
- Access to state-of-the-art hardware and research tools.
Responsibilities
- Design and implement scalable, high-performance AI architectures capable of processing petabytes of data.
- Lead the research and development of proprietary machine learning models, focusing on efficiency and scalability.
- Collaborate with cross-functional teams to integrate AI solutions into complex product ecosystems.
- Optimize model inference and training pipelines for speed and cost-efficiency.
- Mentor junior engineers and establish best practices for AI engineering within the organization.
- Stay at the forefront of emerging AI trends and evaluate their potential for integration into our roadmap.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Minimum of 7 years of professional experience in AI/ML engineering, with at least 3 years in a senior architectural role.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven experience deploying and scaling LLMs and Generative AI models in production environments.
- Strong understanding of distributed systems, cloud infrastructure (AWS/GCP/Azure), and containerization (Kubernetes/Docker).
- Experience with MLOps tools and data pipelines.