Job Description
Are you ready to architect the future of intelligent systems?
We are Nebula AI Solutions, a forward-thinking pioneer in Generative Artificial Intelligence. As we scale our operations to meet the demands of 2026, we are seeking a visionary Senior Generative AI Engineer to lead our technical team in building the next generation of Large Language Models (LLMs) and autonomous agents.
In this pivotal role, you won't just write code; you will define the architecture that powers the future of enterprise automation. You will work in a high-performance environment where innovation is not just encouraged—it is the standard. Join us in Austin, Texas, and help us push the boundaries of what AI can achieve.
Why Join Us?
- Work on cutting-edge RAG (Retrieval-Augmented Generation) systems.
- Competitive equity package and remote-first flexibility.
- Top-tier benefits including health, dental, and vision coverage.
- Access to the latest hardware for model training and fine-tuning.
Responsibilities
- Design, develop, and optimize scalable Generative AI models and LLM architectures.
- Implement and fine-tune large language models using PyTorch and TensorFlow.
- Build robust Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and reduce hallucinations.
- Collaborate with product teams to translate complex business requirements into technical AI solutions.
- Ensure code quality, performance, and scalability across distributed AI systems.
- Conduct rigorous testing, validation, and monitoring of deployed AI models.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related field (or equivalent practical experience).
- 5+ years of experience in Machine Learning, Deep Learning, or Natural Language Processing (NLP).
- Expert proficiency in Python, PyTorch, or JAX.
- Strong understanding of Transformer models, attention mechanisms, and LLM fine-tuning techniques.
- Experience with vector databases (e.g., Pinecone, Milvus, Weaviate) and MLOps tools.
- Proven track record of deploying AI models into production environments.