Job Description
Join the Vanguard of Artificial Intelligence
Nexus Horizon AI is on a mission to engineer the intelligent systems of tomorrow. As we look toward the technological horizon of 2026, we are seeking a visionary Senior Generative AI Engineer to join our elite R&D division in San Francisco. You will be at the forefront of developing next-generation Large Language Models (LLMs) and generative agents that will redefine human-computer interaction.
In this role, you won't just write code; you will architect the future of synthetic intelligence. We offer a competitive equity package, a dynamic work environment, and the opportunity to work on problems that matter.
Why Join Us?
- Impactful Work: Build foundational models that power the next generation of digital experiences.
- Top-Tier Talent: Collaborate with world-class researchers and engineers.
- Future-Ready: Work on cutting-edge architectures designed for the scalability of 2026 and beyond.
Responsibilities
- Design, train, and fine-tune large-scale generative models (GPT, LLaMA, Claude, etc.) to achieve state-of-the-art performance.
- Architect scalable MLOps pipelines for model training, evaluation, and deployment on cloud infrastructure (AWS/GCP).
- Implement advanced Retrieval-Augmented Generation (RAG) strategies to enhance model accuracy and reduce hallucinations.
- Conduct rigorous research on novel architectures including diffusion models, transformers, and multimodal learning.
- Optimize inference latency and resource utilization for real-time generative applications.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
Qualifications
- Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of professional experience in deep learning, machine learning, or natural language processing.
- Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
- Deep understanding of transformer architectures, attention mechanisms, and optimization techniques.
- Experience with distributed training frameworks (Ray, Horovod) and GPU acceleration.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to diverse stakeholders.