Job Description
We are seeking a visionary Senior Generative AI Engineer to join Nebula Dynamics in San Francisco. As a pioneer in the field of artificial intelligence, we are building the next generation of Large Language Models (LLMs) and multimodal systems designed for the future of 2026 and beyond. You will work on high-impact projects that define the standard for AI safety, efficiency, and creativity.
Why Join Us?
We offer a competitive compensation package, fully remote-first flexibility, and the opportunity to work with state-of-the-art hardware and proprietary datasets. If you are passionate about the future of AI and want to shape the technology that will define the coming decade, we want to hear from you.
Core Responsibilities:
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art Generative AI models using transformer architectures and deep learning frameworks.
- Optimization: Optimize model inference latency and throughput for edge deployment and cloud-scale systems.
- Research Implementation: Translate cutting-edge academic research in NLP and LLMs into production-ready code and scalable solutions.
- RAG Architecture: Build robust Retrieval-Augmented Generation pipelines to enhance model accuracy and reduce hallucinations.
- Collaboration: Partner with product managers and engineers to define AI requirements and deliver innovative user features.
- Evaluation: Establish rigorous evaluation frameworks and metrics to measure model performance and safety.
Qualifications:
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field (or equivalent practical experience).
- Experience: 5+ years of experience in machine learning, deep learning, or natural language processing.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Strong understanding of distributed computing and cloud infrastructure (AWS, GCP, or Azure).
- Domain Knowledge: Deep understanding of LLMs, Transformer models, attention mechanisms, and prompt engineering.
- Tools: Experience with Hugging Face, LangChain, Vector Databases (Pinecone, Weaviate), and MLOps tools.
- Communication: Excellent verbal and written communication skills with the ability to explain complex technical concepts to non-technical stakeholders.