Job Description
Are you ready to define the future of technology?
Nebula Dynamics is seeking a visionary Senior AI Architect (2026 Vision) to lead our advanced research division. We are building the infrastructure for tomorrow, focusing on next-generation Generative AI and Large Language Models (LLMs). If you are passionate about pushing the boundaries of what is possible in artificial intelligence, this is your opportunity to shape the roadmap for the year 2026 and beyond.
In this role, you will not just implement existing models; you will architect novel architectures that redefine human-computer interaction. You will work in a high-performance environment with top-tier researchers and engineers dedicated to solving the hardest problems in AI safety, scalability, and efficiency.
Why Join Nebula Dynamics?
- Work on groundbreaking projects with a direct impact on global industries.
- Competitive compensation package including equity and performance bonuses.
- Flexible remote-first culture with access to top-tier tech infrastructure.
- Professional development opportunities in cutting-edge AI research.
Responsibilities
- Architect and deploy scalable Generative AI models aligned with the 2026 product roadmap.
- Lead research initiatives in Large Language Models (LLMs) and multimodal learning.
- Collaborate with product managers and data scientists to translate business needs into technical solutions.
- Optimize model inference latency and reduce computational costs for production deployment.
- Establish best practices for MLOps, data governance, and model monitoring.
- Provide technical mentorship to junior engineers and foster a culture of innovation.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- Minimum of 5 years of professional experience in Machine Learning, Deep Learning, or AI Engineering.
- Expert proficiency in Python, PyTorch, or TensorFlow.
- Strong background in Natural Language Processing (NLP) or Computer Vision.
- Experience deploying models at scale on cloud platforms (AWS, GCP, or Azure).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.