Job Description
Are you ready to architect the intelligence of tomorrow? Nexus Future Systems is pioneering the next generation of Artificial General Intelligence (AGI). We are seeking a visionary Generative AI Engineer to lead the development of cutting-edge Large Language Models (LLMs) and autonomous agents that will define the tech landscape in 2026 and beyond.
In this pivotal role, you won't just be maintaining existing models; you will be building the infrastructure that powers the future of human-computer interaction. You will work at the intersection of deep learning, distributed systems, and creative engineering to deliver products that are not only powerful but also safe, scalable, and ethically sound.
Why join us?
- Work on projects that have a global impact.
- Competitive compensation and equity packages.
- Flexible remote-first culture with a San Francisco hub.
- Access to the latest hardware and cloud resources.
Responsibilities
- Architect and deploy scalable, high-performance LLM infrastructure on cloud platforms (AWS/GCP).
- Design, train, and fine-tune proprietary foundation models using state-of-the-art techniques (LoRA, P-Tuning).
- Develop and optimize Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and reduce hallucinations.
- Implement robust safety guardrails and RLHF techniques to ensure AI reliability and alignment.
- Collaborate with cross-functional product teams to translate technical AI capabilities into user-centric features.
- Mentor a team of data scientists and ML engineers to foster a culture of innovation.
Qualifications
- PhD or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- 5+ years of professional experience in deep learning, NLP, or AI engineering.
- Expert proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, JAX).
- Extensive hands-on experience with Large Language Models (GPT-4, Llama 3, Claude) and fine-tuning methods.
- Strong understanding of distributed systems, MLOps, and containerization (Docker, Kubernetes).
- Excellent communication skills and the ability to explain complex AI concepts to non-technical stakeholders.