Job Description
The Future of Intelligence is Here. Nebula Dynamics is on a mission to pioneer the technological landscape of 2026. We are looking for a visionary Senior AI Architect to lead our advanced research division, focusing on Generative AI, Quantum-Ready systems, and autonomous agent development. If you thrive in a high-velocity, cutting-edge environment and want to define the next era of computing, we want to meet you.
As a key member of our leadership team, you will bridge the gap between theoretical research and production-grade deployment. You will architect scalable neural networks, optimize large language models for edge computing, and guide a team of elite engineers toward our 2026 strategic goals.
Why Join Nebula Dynamics?
- Work on Next-Gen AI that will shape the future of enterprise.
- Competitive compensation package with equity opportunities.
- State-of-the-art facilities and top-tier hardware access.
- Flexible remote-first culture with premium tech benefits.
Responsibilities
- Design and implement scalable AI/ML infrastructure capable of handling petabyte-scale data streams.
- Lead the architectural roadmap for Generative AI models, ensuring alignment with the 2026 Vision strategy.
- Optimize model inference speed and reduce computational costs through advanced pruning and quantization techniques.
- Collaborate with cross-functional teams (Data Science, Product, DevOps) to integrate AI solutions into core products.
- Establish best practices for MLOps, model governance, and ethical AI usage.
- Mentor junior architects and engineers, fostering a culture of continuous innovation.
- Stay ahead of industry trends in Quantum Computing and Neuromorphic engineering.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Minimum of 7+ years of experience in AI/ML engineering, with at least 3 years in a senior architectural role.
- Expert proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (Ray, Spark).
- Deep understanding of Large Language Models (LLMs), fine-tuning, and RAG architectures.
- Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Proven track record of deploying production-grade AI systems with high availability.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.