Job Description
Are you ready to architect the intelligence of tomorrow? Nebula Core Technologies is pioneering the next generation of generative AI systems, and we are seeking a visionary Senior AI Architect to lead our R&D efforts. You will be at the forefront of developing scalable, efficient, and ethical AI models designed to redefine human-computer interaction in the 2026 era.
In this role, you will not just write code; you will define architectural paradigms that will power enterprise-grade applications globally. We offer a competitive compensation package, equity packages, and a culture that prioritizes innovation and impact.
Why Join Us?
- Work on cutting-edge LLMs and diffusion models.
- Competitive salary and equity in a Series B startup.
- Flexible remote-first culture with quarterly in-person meetups.
- Top-tier medical, dental, and vision coverage.
The Role:
We are looking for a leader who can bridge the gap between theoretical research and production deployment. You will own the technical vision for our AI infrastructure, ensuring our models are robust, secure, and capable of handling massive scale.
Responsibilities
- Design and implement scalable machine learning pipelines and architectures for Large Language Models (LLMs).
- Lead the research and optimization of model inference to reduce latency and improve throughput.
- Collaborate with cross-functional teams of engineers, product managers, and designers to translate research into product features.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Evaluate and integrate new state-of-the-art algorithms into our existing tech stack.
- Ensure data privacy, model fairness, and ethical AI practices in all deployments.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related technical field (or equivalent practical experience).
- 5+ years of professional experience in AI/ML engineering, with a strong focus on Deep Learning.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Deep understanding of Natural Language Processing (NLP) and Transformer architectures.
- Experience with MLOps tools (Docker, Kubernetes, MLflow) and cloud platforms (AWS, GCP, or Azure).
- Strong problem-solving skills with the ability to debug complex distributed systems.
- Excellent communication skills and the ability to articulate technical concepts to non-technical stakeholders.