Job Description
Join the Pioneers of the AI Revolution
Nexus Horizon Systems is at the forefront of the 2026 technology landscape, building next-generation intelligence for enterprise solutions. We are seeking a visionary Senior Generative AI Architect to design and deploy cutting-edge Large Language Model (LLM) infrastructures that redefine human-computer interaction. If you are passionate about the future of AI and want to work in a high-performance, high-impact environment, we want to hear from you.
Why Join Us?
- Impactful Work: Build the foundational models that will power the next decade of technology.
- Top-Tier Compensation: Competitive salary and equity packages in the heart of Silicon Valley.
- Modern Tech Stack: Access to the latest GPUs, cloud infrastructure, and open-source frameworks.
Responsibilities
- Model Architecture: Design and implement scalable generative AI architectures, focusing on LLM fine-tuning, RAG (Retrieval-Augmented Generation), and prompt engineering.
- Performance Optimization: Optimize model inference speeds and reduce latency for real-time applications.
- Data Pipeline Management: Build robust data pipelines to curate high-quality training data and fine-tuning datasets.
- Collaboration: Partner with product managers, data scientists, and engineers to translate business requirements into technical AI solutions.
- Research: Stay ahead of the curve by integrating the latest advancements in Generative AI research into our production systems.
- Deployment: Oversee the deployment of AI models to cloud environments (AWS/GCP) ensuring security and compliance.
Qualifications
- Experience: 5+ years of experience in software engineering, machine learning engineering, or data science with a focus on NLP.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and Hugging Face Transformers.
- LLM Knowledge: Proven track record of working with or fine-tuning large language models (GPT-4, Llama 3, Claude, etc.).
- System Design: Strong understanding of system design principles, API development, and microservices architecture.
- Tools: Proficiency with version control (Git), CI/CD pipelines, and containerization (Docker/Kubernetes).
- Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.