Job Description
Are you ready to architect the AI landscape of 2026?
Nebula Horizon is at the forefront of the generative revolution. We are seeking a visionary Senior Generative AI Engineer to lead the development of our next-generation Large Language Models (LLMs) and autonomous agent frameworks. In this pivotal role, you will bridge the gap between cutting-edge research and production-grade deployment, directly shaping the future of human-computer interaction.
Join a team of elite engineers and researchers dedicated to pushing the boundaries of what's possible. You will not just build models; you will define the architecture that drives our 2026 strategic roadmap and sets new industry standards for efficiency, accuracy, and scalability.
Why Join Us?
- Work with state-of-the-art hardware (NVIDIA H100 clusters).
- Competitive equity package and performance bonuses.
- Flexible remote-first culture with premium San Francisco perks.
- Direct impact on products used by millions globally.
Responsibilities
- Model Architecture & Training: Design and implement scalable training pipelines for Large Language Models, focusing on fine-tuning, instruction tuning, and reinforcement learning from human feedback (RLHF).
- RAG & Vector Systems: Build robust Retrieval-Augmented Generation (RAG) systems to enhance model accuracy and reduce hallucinations in real-world applications.
- Optimization & Inference: Optimize model inference for latency and throughput, utilizing quantization, pruning, and efficient attention mechanisms to deploy models on edge devices.
- Collaboration: Partner with product managers and data scientists to translate complex business requirements into technical AI solutions.
- Research: Stay ahead of the curve by integrating the latest advancements in Transformer architectures and multimodal learning into our core stack.
- Mentorship: Mentor junior engineers and data scientists, fostering a culture of continuous learning and innovation.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field (or equivalent practical experience).
- Technical Mastery: Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Experience: 5+ years of experience in machine learning, specifically in NLP and deep learning.
- Frameworks: Proficiency with Hugging Face Transformers, LangChain, and vector databases (Pinecone, Milvus, Weaviate).
- Production Experience: Proven track record of deploying large-scale ML models to production environments (AWS, GCP, or Azure).
- Problem Solving: Strong analytical skills with a passion for solving complex, ambiguous problems.