Job Description
Join the Architects of the Future
Nexus Horizon is at the forefront of the AI revolution, building the foundational models that will define the 2026 era. We are seeking a visionary Senior Generative AI Engineer to lead our advanced research division. You will be responsible for designing, training, and deploying next-generation Large Language Models (LLMs) and multimodal systems that push the boundaries of what is possible.
If you are passionate about shaping the trajectory of artificial intelligence and want to work in a high-performance environment, we want to hear from you.
Responsibilities
- Model Architecture & Development: Design and implement novel generative AI architectures, focusing on scaling efficiency and hallucination reduction.
- Training Pipelines: Build and optimize large-scale training pipelines using distributed computing frameworks (PyTorch, JAX) to train models from scratch or fine-tune existing state-of-the-art models.
- RAG & Optimization: Develop sophisticated Retrieval-Augmented Generation (RAG) systems and model quantization techniques to ensure optimal performance on edge devices.
- Collaboration: Partner with product teams to translate complex technical requirements into scalable, production-ready AI solutions.
- MLOps: Implement robust CI/CD pipelines for machine learning models, ensuring continuous integration and deployment of high-quality code.
- Research: Stay ahead of the curve by researching the latest academic papers and integrating breakthroughs into our product roadmap.
Qualifications
- Education: MS or PhD in Computer Science, Mathematics, or a related field with a focus on Deep Learning.
- Experience: 5+ years of professional experience in Machine Learning, with at least 2 years specifically in Generative AI or LLMs.
- Technical Skills: Proficiency in Python, C++, and frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers.
- System Knowledge: Deep understanding of distributed training, attention mechanisms, and transformer architectures.
- Tools: Experience with cloud platforms (AWS/GCP/Azure) and containerization tools (Docker, Kubernetes).
- Communication: Excellent ability to communicate complex technical concepts to non-technical stakeholders.