Job Description
Join the vanguard of the Artificial Intelligence revolution. Nexus Horizon Labs is seeking a visionary Senior AI/LLM Engineer to architect the next generation of generative models. If you are passionate about pushing the boundaries of Large Language Models (LLMs), fine-tuning foundation models, and deploying scalable AI solutions, we want to hear from you.
In this role, you will not just use existing tools; you will help build them. You will work in a collaborative, high-performance environment focused on ethical AI, advanced NLP, and multimodal systems. Be part of a team that is defining the standard for AI in 2026 and beyond.
Why Join Us?
- Work with state-of-the-art hardware (NVIDIA H100 clusters).
- Competitive compensation package and equity.
- Flexible remote-first culture with premium office amenities in SF.
- Opportunity to publish research and impact millions of users.
Responsibilities
- Model Architecture & Training: Design and implement novel architectures for Large Language Models, including transformers and diffusion models, optimizing for performance and accuracy.
- Fine-Tuning & Optimization: Lead the fine-tuning process of open-source LLMs (e.g., Llama 3, Mistral) and proprietary models to achieve specific domain expertise.
- RAG Implementation: Develop robust Retrieval-Augmented Generation pipelines to enhance model accuracy and reduce hallucinations.
- Production Deployment: Deploy AI models to production environments using containerization (Docker/Kubernetes) and MLOps best practices.
- Performance Engineering: Conduct rigorous testing to optimize inference latency and reduce memory footprint for edge and cloud deployment.
- Research & Innovation: Stay ahead of the curve by exploring cutting-edge research papers and integrating new methodologies into our product suite.
- Collaboration: Partner with data scientists, product managers, and engineers to translate complex AI concepts into user-friendly features.
Qualifications
- Education: MS or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of professional experience in software engineering or machine learning, with at least 2 years dedicated to Deep Learning and NLP.
- Programming: Expert proficiency in Python and C++. Strong understanding of GPU programming (CUDA) is highly preferred.
- Frameworks: Extensive experience with PyTorch, TensorFlow, and Hugging Face Transformers.
- Model Engineering: Deep knowledge of model architecture, training strategies, and optimization techniques.
- Problem Solving: Ability to debug complex distributed training issues and optimize resource utilization.
- Communication: Excellent verbal and written communication skills, with the ability to articulate technical concepts to non-technical stakeholders.