Job Description
Join the Architects of Tomorrow.
Nebula Core Systems is seeking a visionary Senior AI Architect to lead the development of next-generation artificial intelligence solutions. As we prepare for the paradigm shifts of 2026, we are looking for a technical leader who can bridge the gap between theoretical AI potential and practical, scalable deployment. You will be at the forefront of integrating Large Language Models, autonomous agents, and predictive analytics into our core enterprise infrastructure.
This is not just a job; it is a mission to engineer the future of human-machine interaction. You will work in a high-performance environment with top-tier talent, leveraging cutting-edge frameworks to solve complex problems.
Why join Nebula Core?
- Competitive compensation package reflecting your expertise.
- Equity and profit-sharing opportunities.
- Flexible remote and hybrid work policies.
- Access to the latest hardware and research tools.
Responsibilities
- Architect and deploy advanced Machine Learning models, focusing on scalability and efficiency for 2026 standards.
- Lead the design of neural network architectures for natural language processing and computer vision.
- Collaborate with cross-functional teams to integrate AI capabilities into existing software ecosystems.
- Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Optimize model inference pipelines to reduce latency and improve throughput.
- Stay abreast of the latest breakthroughs in AI research and implement relevant methodologies.
- Conduct rigorous testing and validation to ensure model robustness and safety.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related quantitative field.
- 8+ years of professional experience in software engineering, with at least 5 years in AI/ML development.
- Deep proficiency in Python, PyTorch, and TensorFlow.
- Strong understanding of Deep Learning principles, NLP, and Generative AI models.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Demonstrated ability to lead technical projects from conception to production deployment.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.