Job Description
We are at the precipice of a new era in computing. Nebula Horizon Systems is looking for a Senior Generative AI Engineer to architect the intelligent infrastructure of tomorrow. If you are passionate about pushing the boundaries of Large Language Models (LLMs), Reinforcement Learning from Human Feedback (RLHF), and autonomous agents, this is your stage.
In this role, you will not just maintain existing models; you will pioneer the next generation of AI architectures designed for 2026 and beyond. You will work in a high-performance environment, collaborating with world-class researchers and engineers to build systems that understand, reason, and create.
Why join us?
- Impact: Shape the future of human-AI interaction on a global scale.
- Equity: Competitive stake in the company’s growth.
- Environment: Top-tier tech stack, flexible remote/hybrid culture, and continuous learning opportunities.
Responsibilities
- Architect LLM Pipelines: Design and implement scalable, efficient, and secure inference pipelines for large-scale generative models.
- Model Optimization: Apply techniques such as quantization, distillation, and pruning to optimize model performance and latency.
- RAG Development: Lead the development of Retrieval-Augmented Generation systems to enhance factual accuracy and reduce hallucinations.
- Research & Experimentation: Stay ahead of the curve by researching and integrating cutting-edge advancements in AI safety and alignment.
- System Integration: Integrate AI models into complex software ecosystems and real-time applications.
Qualifications
- Education: MS or PhD in Computer Science, Mathematics, or a related technical field.
- Experience: 5+ years of professional experience in machine learning, deep learning, or natural language processing.
- Tech Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX. Deep experience with Hugging Face Transformers.
- AI Specialization: Strong understanding of Transformer architectures, fine-tuning strategies, and LLM evaluation metrics.
- Tools: Experience with vector databases (Pinecone, Milvus), Kubernetes, and cloud platforms (AWS/GCP).