Job Description
Are you ready to architect the intelligent systems of tomorrow? Nexus Future Labs is seeking a visionary Senior Generative AI Engineer to lead our next-generation AI initiatives. As we look toward 2026, we are building the infrastructure that will define the future of human-machine interaction.
In this pivotal role, you won't just be maintaining models; you will be architecting the next evolution of Large Language Models (LLMs) and Generative Adversarial Networks (GANs). You will work with a world-class team of researchers and engineers to deploy scalable, ethical, and high-performance AI solutions that solve complex real-world problems.
Why Join Us?
- Work on cutting-edge AI research with direct impact on industry standards.
- Competitive equity package and comprehensive benefits.
- Flexible hybrid work environment in the heart of San Francisco.
- Access to state-of-the-art computing infrastructure.
Responsibilities
- Architect and optimize large-scale generative models for high-traffic production environments.
- Develop and fine-tune foundation models (e.g., LLaMA, GPT variants) for specialized enterprise applications.
- Design robust data pipelines for training and evaluation, ensuring high data quality and privacy compliance.
- Collaborate with product teams to integrate AI capabilities into user-facing products seamlessly.
- Ensure model explainability, fairness, and safety standards are met through rigorous testing.
- Stay at the bleeding edge of AI research, implementing cutting-edge techniques such as RAG, Fine-tuning, and Prompt Engineering.
Qualifications
- PhD or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Expert proficiency in Python, PyTorch, or TensorFlow.
- Deep understanding of transformer architectures and LLM fine-tuning methodologies.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Strong background in MLOps, CI/CD, and model deployment strategies.