Job Description
Are you ready to architect the AI landscape of 2026?
Nexus Horizon Solutions is at the forefront of the next industrial revolution. We are seeking a visionary Senior Generative AI Engineer to lead the development of next-generation Large Language Models (LLMs) and multimodal AI systems. If you are passionate about pushing the boundaries of what is possible in artificial intelligence and want to shape the future of enterprise automation, we want to hear from you.
In this role, you won't just be maintaining legacy systems; you will be building the core infrastructure that will define how businesses interact with machines in the coming years. Join a world-class team of researchers and engineers dedicated to ethical, scalable, and transformative AI.
Responsibilities
- Lead AI Architecture: Design and deploy robust, scalable generative AI models, focusing on Large Language Models (LLMs) and transformer architectures.
- RAG & Fine-Tuning: Spearhead the implementation of Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and reduce hallucinations.
- Model Optimization: Optimize inference latency and cost-efficiency for high-volume production environments using quantization and model pruning techniques.
- Research & Innovation: Stay ahead of the curve regarding emerging AI trends in 2026, evaluating new architectures like MoE (Mixture of Experts) and self-supervised learning methods.
- Collaboration: Partner with product managers and data scientists to translate complex technical requirements into production-ready AI solutions.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in AI/ML engineering, with a focus on Natural Language Processing (NLP).
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and Hugging Face Transformers.
- Model Knowledge: Deep understanding of GPT architectures, Llama, and state-of-the-art generative models.
- System Design: Strong experience with cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes).