Job Description
We are standing at the edge of a new era. Nebula Core Systems is building the foundational architecture for the year 2026 and beyond. We are looking for a visionary Senior AI Research Engineer to lead our advanced generative modeling initiatives. In this role, you won't just be maintaining existing systems; you will pioneer the next generation of Artificial General Intelligence (AGI) technologies that will define the future of enterprise automation.
You will work in a high-performance environment where theoretical research meets real-world application. If you are passionate about solving complex problems at the intersection of deep learning, natural language processing, and cognitive architectures, this is your opportunity to shape the trajectory of technology.
You will work in a high-performance environment where theoretical research meets real-world application. If you are passionate about solving complex problems at the intersection of deep learning, natural language processing, and cognitive architectures, this is your opportunity to shape the trajectory of technology.
Responsibilities
- Design and implement cutting-edge deep learning models, focusing on LLMs and reinforcement learning agents.
- Lead research initiatives to improve model accuracy, efficiency, and scalability for production environments.
- Collaborate with cross-functional engineering teams to translate theoretical AI concepts into robust, production-ready software.
- Optimize neural network architectures for low-latency inference on distributed cloud infrastructure.
- Mentor junior data scientists and engineers, fostering a culture of innovation and technical excellence.
- Stay abreast of the latest academic research and industry trends to drive the roadmap for 2026 technologies.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, Statistics, or a related technical field.
- Minimum of 5 years of professional experience in machine learning engineering and research.
- Extensive proficiency in Python, PyTorch, or TensorFlow.
- Strong experience with distributed computing systems (Kubernetes, Docker, AWS/GCP/Azure).
- Deep understanding of statistical methods, probability theory, and optimization algorithms.
- Proven track record of publishing research or contributing to open-source AI projects.