Job Description
Are you ready to architect the intelligence of tomorrow?
Nexus Future Labs is seeking a visionary Senior Generative AI Engineer to lead our cutting-edge research and deployment of next-generation Large Language Models (LLMs) and Autonomous AI Agents.
In this pivotal role, you won't just be implementing existing models; you will be defining the roadmap for AI capabilities in the 2026 era. We are building the foundation for a future where human and machine intelligence seamlessly collaborate.
Why Join Us?
- Impactful Work: Your code will shape the core technology used by millions.
- Premium Compensation: Competitive salary, equity packages, and comprehensive benefits.
- Cutting-Edge Stack: Work with the latest in PyTorch, LangChain, and proprietary cloud infrastructure.
- Remote-First Culture: Collaborate with top-tier talent from around the globe.
Key Responsibilities:
- Design, train, and fine-tune large-scale foundation models tailored for enterprise-grade applications.
- Architect robust Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and context.
- Develop autonomous AI agents capable of complex reasoning and multi-step task execution.
- Optimize model inference latency and cost-efficiency for real-time production environments.
- Collaborate with product managers and data scientists to translate business requirements into technical solutions.
Qualifications:
- PhD or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- 5+ years of professional experience in Python, TensorFlow, or PyTorch.
- Proven expertise in Natural Language Processing (NLP) and deep learning architectures.
- Experience deploying models via Kubernetes, Docker, and cloud-native services.
- Strong understanding of ethics in AI, bias mitigation, and responsible AI practices.
Responsibilities
- Design, train, and fine-tune large-scale foundation models tailored for enterprise-grade applications.
- Architect robust Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and context.
- Develop autonomous AI agents capable of complex reasoning and multi-step task execution.
- Optimize model inference latency and cost-efficiency for real-time production environments.
- Collaborate with product managers and data scientists to translate business requirements into technical solutions.
Qualifications
- PhD or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- 5+ years of professional experience in Python, TensorFlow, or PyTorch.
- Proven expertise in Natural Language Processing (NLP) and deep learning architectures.
- Experience deploying models via Kubernetes, Docker, and cloud-native services.
- Strong understanding of ethics in AI, bias mitigation, and responsible AI practices.