Job Description
Join Nebula AI Labs, a pioneering force in the generative AI space, where we are redefining human-machine interaction. We are seeking a visionary Senior AI Research Scientist to lead our next-generation language model initiatives. You will work in a high-performance environment, collaborating with top-tier engineers and researchers to push the boundaries of what is possible with Large Language Models (LLMs).
Why join us?
- Work with state-of-the-art hardware (NVIDIA A100/H100 clusters).
- Competitive compensation package and equity options.
- Flexible remote-first culture with a hub in the heart of San Francisco.
If you are passionate about transformer architectures, fine-tuning strategies, and ethical AI alignment, we want to hear from you.
Responsibilities
- Model Development: Design, implement, and optimize state-of-the-art generative models, specifically focusing on LLMs and diffusion models.
- Research & Innovation: Conduct rigorous research to improve model accuracy, coherence, and safety, publishing findings in top-tier conferences (NeurIPS, ICML, ACL).
- Technical Leadership: Mentor junior researchers and engineers, providing technical guidance and conducting code reviews to maintain high engineering standards.
- Deployment: Collaborate with MLOps engineers to deploy models into production environments, ensuring scalability and low-latency inference.
- Data Strategy: Curate and preprocess massive datasets, implementing data pipelines to enhance model training efficiency.
Qualifications
- Education: PhD in Computer Science, Statistics, Mathematics, or a related field, with a focus on Machine Learning, Deep Learning, or Natural Language Processing.
- Experience: 5+ years of professional experience in AI/ML research or a strong academic background with significant publication history.
- Technical Skills: Deep proficiency in Python, PyTorch, or TensorFlow. Extensive experience with Transformer architectures (BERT, GPT, T5).
- Tools: Familiarity with Hugging Face, LangChain, and distributed training frameworks (Ray, Horovod).
- Problem Solving: Demonstrated ability to tackle complex mathematical and algorithmic challenges.