Job Description
Shape the Future of Intelligence at Nexus Future Labs
Welcome to Nexus Future Labs, a pioneer in the next generation of artificial intelligence. We are building the foundational systems for the year 2026 and beyond, specializing in Large Language Models (LLMs) and autonomous agents. We are seeking a visionary Senior Generative AI Engineer to join our elite engineering team in San Francisco.
In this pivotal role, you will not just write code; you will architect the cognitive frameworks that will define human-computer interaction for the next decade. You will work with cutting-edge hardware and proprietary datasets to push the boundaries of Natural Language Processing (NLP).
Join us in creating the AI that will power the future.
Responsibilities
Architect LLM Systems: Design and implement scalable, high-performance generative models using PyTorch and JAX.Model Optimization: Apply techniques such as quantization, pruning, and distillation to optimize models for production deployment.Retrieval-Augmented Generation (RAG): Build robust RAG pipelines to enhance model accuracy and reduce hallucinations.Ethical AI & Safety: Develop and implement safety protocols and bias mitigation strategies for generative outputs.Research Integration: Translate cutting-edge academic research from top-tier conferences (NeurIPS, ICML) into production-ready code.Collaboration: Partner with product managers and designers to build intuitive interfaces for complex AI models.
Qualifications
Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.Experience: 5+ years of professional experience in deep learning and NLP.Technical Skills: Expert proficiency in Python, C++, and at least one deep learning framework (PyTorch, TensorFlow, or JAX).Research: A strong publication record in top AI conferences (NeurIPS, ACL, EMNLP) is highly preferred.Architecture: Deep understanding of transformer architectures, attention mechanisms, and vector databases.Tools: Experience with cloud platforms (AWS/GCP), Docker, and Kubernetes.