Job Description
We are at the precipice of a new era in artificial intelligence. At Nebula AI Labs, our mission is to define the standards for the year 2026 and beyond. We are seeking a visionary Senior AI Research Engineer to join our elite team and lead the development of scalable, safe, and superintelligent generative models.
In this role, you will move beyond standard Machine Learning and delve into the frontiers of Large Language Models (LLMs), multimodal architectures, and ethical AI deployment. You will work in a high-performance environment that demands technical excellence and a relentless pursuit of innovation.
Why Join Us?
We offer top-tier compensation, equity packages, and the opportunity to work on projects that will fundamentally reshape human-computer interaction.
Responsibilities
- Architect Next-Gen Models: Lead the design and implementation of advanced Transformer architectures and generative AI models capable of zero-shot reasoning and complex task execution.
- Optimization & Scaling: Engineer efficient inference pipelines and optimize model training workflows to handle petabyte-scale datasets on distributed GPU clusters.
- Research Leadership: Publish high-impact papers, contribute to open-source communities, and drive internal research initiatives aligned with the 2026 AI roadmap.
- RAG & Knowledge Management: Develop and refine Retrieval-Augmented Generation (RAG) systems to enhance factual accuracy and reduce hallucination in AI outputs.
- AI Safety & Ethics: Implement robust guardrails and safety protocols to ensure AI deployments are transparent, unbiased, and secure.
- Collaboration: Partner with cross-functional teams including product managers, engineers, and ethicists to translate research breakthroughs into market-ready products.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, Statistics, or a related field, with a focus on Deep Learning or Artificial Intelligence.
- Experience: 5+ years of professional experience in machine learning research or engineering, with at least 2 years specifically focused on Large Language Models (LLMs) or Generative AI.
- Technical Stack: Proficiency in Python, PyTorch or TensorFlow, and CUDA programming. Experience with distributed training frameworks (e.g., Ray, DeepSpeed, Megatron-LM) is required.
- Research Skills: Strong background in statistical analysis, natural language processing (NLP), and cognitive science principles.
- Communication: Exceptional ability to communicate complex technical concepts to both technical and non-technical stakeholders.
- Passion: Deep curiosity about the future of AI and a track record of pushing the boundaries of what is currently possible.