Job Description
We are at the forefront of the AI revolution, and we are looking for a visionary Senior Generative AI Engineer to join our elite team in San Francisco. At Nexus 2026, we are building the operating system for the future, leveraging cutting-edge Large Language Models (LLMs) and diffusion models to redefine human-computer interaction. If you are passionate about pushing the boundaries of what is possible with AI and want to work in a high-impact, innovative environment, we want to hear from you.
Why Join Us?
- Work with state-of-the-art technology and industry leaders.
- Competitive compensation and equity packages.
- Flexible remote-first culture with a premium San Francisco office.
- Opportunity to shape the AI landscape for the next decade.
Responsibilities
- Model Development: Design, train, and fine-tune large-scale generative models (e.g., GPT-4, Llama 3, Claude) for specific enterprise applications.
- Pipeline Optimization: Build scalable, high-performance inference pipelines to handle millions of requests per day with low latency.
- Research & Innovation: Stay ahead of the curve by exploring novel architectures and techniques in NLP and multimodal learning.
- Collaboration: Partner with product managers, designers, and engineers to translate complex AI capabilities into intuitive user experiences.
- RAG Implementation: Develop and implement Retrieval-Augmented Generation (RAG) systems to ensure factual accuracy and reduce hallucinations.
- Code Review: Maintain high standards of code quality and best practices within the engineering team.
Qualifications
- Education: M.S. or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in software engineering with a strong focus on AI/ML.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX; experience with Hugging Face Transformers and LangChain.
- Knowledge: Deep understanding of NLP concepts, transformer architectures, and optimization techniques (quantization, distillation).
- Deployment: Experience deploying models to production environments (AWS, GCP, or Azure).
- Communication: Excellent verbal and written communication skills, capable of explaining complex technical concepts to non-technical stakeholders.