Job Description
Are you ready to define the future of artificial intelligence?
Nebula Dynamics is pioneering the next generation of sentient computing, and we are looking for a visionary Senior AI Research Engineer to join our elite team. As we approach the critical 2026 milestone for Artificial General Intelligence (AGI), you will be at the forefront of developing scalable neural architectures and ethical AI frameworks.
We are not just building models; we are architecting the intelligence of tomorrow. If you thrive in a fast-paced, high-impact environment and possess a deep understanding of large language models and reinforcement learning, we want to hear from you.
Why Nebula Dynamics?
- Work on cutting-edge AGI research.
- Competitive compensation and equity packages.
- Flexible remote-first culture with top-tier equipment.
Responsibilities
- Lead the design and implementation of novel neural network architectures aimed at achieving AGI capabilities by 2026.
- Conduct high-impact research in machine learning, specifically focusing on scalability, efficiency, and interpretability.
- Optimize large-scale model inference and training pipelines to reduce computational costs.
- Collaborate with cross-functional teams of engineers, ethicists, and product managers to deploy responsible AI solutions.
- Publish research findings in top-tier conferences (NeurIPS, ICML, etc.) and contribute to open-source communities.
- Mentor junior researchers and engineers, fostering a culture of innovation and continuous learning.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- 5+ years of professional experience in machine learning, deep learning, or AI research.
- Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of publishing research or deploying large-scale ML models.
- Deep understanding of Natural Language Processing (NLP), Computer Vision, or Multi-modal learning.
- Experience with cloud infrastructure (AWS, GCP) and distributed training systems.