Job Description
The Future is Now. Nexus Horizon Technologies is at the forefront of the next technological revolution. We are seeking a visionary Senior AI/LLM Engineer to join our elite team in San Francisco. As we look toward 2026, we are building the infrastructure for the next generation of Artificial General Intelligence (AGI) and Autonomous Agents.
In this role, you will not just use existing tools; you will help define the standards for the future. You will work on cutting-edge generative models, fine-tuning algorithms, and scalable inference pipelines that will power the digital world of tomorrow.
Why Join Us?
We offer a competitive salary, equity package, and the opportunity to work in a state-of-the-art facility in the heart of Silicon Valley. You will have direct access to senior leadership and the autonomy to drive technical decisions.
Responsibilities
- Architect Scalable AI Solutions: Design and implement robust, high-performance Large Language Model (LLM) applications and autonomous agent frameworks for enterprise clients.
- Model Optimization: Fine-tune and optimize pre-trained models (e.g., GPT-4, LLaMA) on proprietary datasets to achieve superior accuracy and reduced latency.
- Inference Engineering: Build and deploy efficient inference pipelines using distributed computing and GPU clusters to handle high-volume requests in real-time.
- RAG Implementation: Develop advanced Retrieval-Augmented Generation architectures to ensure factual accuracy and context-aware responses in AI systems.
- Research & Development: Stay ahead of the curve by researching emerging AI paradigms, contributing to internal patents, and presenting findings to the engineering team.
Qualifications
- Education: Master’s degree in Computer Science, Mathematics, or a related field; PhD preferred.
- Experience: 5+ years of professional experience in AI/ML, Deep Learning, or Software Engineering with a focus on NLP.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and modern NLP libraries (Hugging Face, spaCy).
- Infrastructure: Strong understanding of cloud architecture (AWS/Azure/GCP) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Demonstrated ability to tackle complex mathematical and algorithmic challenges in large-scale systems.