Job Description
Are you ready to define the future of intelligent systems?
Nexus AI Labs is pioneering the next generation of Large Language Models (LLMs) and generative AI solutions. We are seeking a visionary Senior Generative AI Engineer to join our elite research and engineering team in San Francisco. If you have a passion for pushing the boundaries of machine learning and want to build transformative AI applications that impact millions, we want to hear from you.
In this role, you will collaborate with world-class researchers and engineers to develop state-of-the-art foundation models, optimize inference pipelines, and deploy scalable AI systems. You will work in a dynamic environment that rewards innovation, technical excellence, and creative problem-solving.
Why Join Us?
- Work on cutting-edge Generative AI and LLM technologies.
- Competitive compensation and equity package.
- Flexible remote-first culture with a hub in the heart of San Francisco.
- Access to top-tier hardware and cloud resources for research.
Responsibilities
- Model Development: Design, train, and fine-tune large-scale generative models using Transformer architectures and modern deep learning frameworks.
- Optimization: Implement efficient inference pipelines and optimize model performance for speed and latency in production environments.
- RAG Implementation: Develop and deploy Retrieval-Augmented Generation (RAG) systems to enhance model accuracy and reduce hallucinations.
- Research: Stay at the forefront of the AI landscape, exploring new techniques in prompt engineering, reinforcement learning from human feedback (RLHF), and multimodal learning.
- Deployment: Collaborate with MLOps engineers to ensure reliable, scalable, and secure deployment of AI models into cloud infrastructure (AWS/GCP).
- Code Review: Conduct rigorous code reviews and mentor junior engineers to maintain high engineering standards across the team.
Qualifications
- Experience: 5+ years of professional experience in machine learning, natural language processing (NLP), or deep learning.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow. Strong understanding of transformer models (BERT, GPT, T5).
- Education: MS or PhD in Computer Science, Mathematics, or a related field.
- Programming: Solid experience with SQL, NoSQL databases, and API development.
- Soft Skills: Excellent communication skills with the ability to translate complex technical concepts for non-technical stakeholders.
- Tools: Familiarity with version control (Git), CI/CD pipelines, and containerization (Docker, Kubernetes).