Job Description
We are looking for a visionary Generative AI Architect to lead our R&D division into the future. As we prepare for the technological paradigm shift of 2026, 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 in artificial intelligence.
In this role, you won't just be using existing tools; you will be architecting the infrastructure that supports autonomous agents, real-time generative content creation, and advanced reasoning capabilities. Join a team of elite engineers and researchers dedicated to solving the most complex challenges in AI safety, scalability, and creativity.
Why Join Nebula Future Tech?
- Shape the Future: Work on cutting-edge projects that define the AI landscape of the next decade.
- Elite Team: Collaborate with world-class researchers and top-tier engineering talent.
- Competitive Compensation: Comprehensive benefits package including equity and performance bonuses.
Responsibilities
- Design and implement proprietary Generative AI architectures, including Transformer-based models and diffusion systems.
- Optimize model inference pipelines for low-latency, high-throughput environments at scale.
- Lead research initiatives in Reinforcement Learning from Human Feedback (RLHF) and Constitutional AI.
- Collaborate with cross-functional teams to integrate AI models into consumer-facing products.
- Ensure ethical AI practices and mitigate biases in generative outputs.
- Mentor junior engineers and data scientists on advanced machine learning techniques.
Qualifications
- Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
- 7+ years of experience in machine learning engineering, specifically with Deep Learning frameworks (PyTorch, TensorFlow, JAX).
- Proven experience training and fine-tuning large-scale LLMs (e.g., GPT-4, LLaMA, Claude architectures).
- Strong understanding of distributed systems, GPU optimization, and model serving (vLLM, TGI, Ray).
- Experience with prompt engineering, RAG (Retrieval-Augmented Generation), and agent orchestration.
- Excellent communication skills and the ability to translate complex technical concepts for diverse stakeholders.