Job Description
We are seeking a visionary Senior AI Research Scientist to join our elite team in San Francisco. As we define the trajectory of Generative AI for the future, you will be at the forefront of developing next-generation Large Language Models (LLMs) and multimodal systems that will redefine human-machine interaction.
At Nexus Future AI, we don't just build software; we engineer the future. If you are passionate about pushing the boundaries of machine learning, optimizing model efficiency, and solving complex problems at scale, we want to hear from you.
Why Join Us?
- Work with state-of-the-art hardware and proprietary datasets.
- Competitive compensation and equity packages.
- Flexible remote-first culture with a vibrant San Francisco hub.
Ready to shape the future? Apply today.
Responsibilities
- Lead the end-to-end research and development of proprietary Generative AI models, focusing on LLMs and diffusion techniques.
- Design and implement novel training algorithms to improve model accuracy, hallucination rates, and reasoning capabilities.
- Collaborate closely with our product engineering teams to deploy models into production environments with a focus on low-latency inference.
- Conduct rigorous experimentation and A/B testing to validate new model architectures and training strategies.
- Mentor junior researchers and data scientists, fostering a culture of innovation and continuous learning.
- Stay abreast of the latest academic research in NLP and Deep Learning to integrate cutting-edge techniques into our pipeline.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of experience in Machine Learning research, specifically within NLP or Generative AI domains.
- Deep expertise in deep learning frameworks such as PyTorch, TensorFlow, or JAX.
- Proven track record of publishing research at top-tier conferences (NeurIPS, ICML, ACL, ICLR).
- Strong proficiency in Python and C++ for high-performance computing and model optimization.
- Experience with model quantization, distillation, and serving infrastructure.