Job Description
Join the Future of Intelligence
We are seeking a visionary Senior Generative AI Engineer to lead the development of next-generation artificial intelligence systems at Nexus Future Labs. In this pivotal role, you will architect and deploy scalable Large Language Models (LLMs) and multimodal AI solutions that will define the technological landscape of 2026 and beyond.
Why This Role?
As we stand on the precipice of the AI revolution, you will have the unique opportunity to shape the tools that will define human-computer interaction for the coming decade. We offer a competitive package, a remote-first culture, and the autonomy to experiment with cutting-edge research.
Key Responsibilities
Architect and train state-of-the-art foundation models using PyTorch and TensorFlow. Optimize model inference latency and reduce token generation costs for production environments. Design and implement Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and context awareness. Collaborate with product managers and data scientists to translate business requirements into technical AI solutions. Conduct rigorous experimentation and evaluation of model performance using established benchmarks. Mentor junior engineers and contribute to the engineering team's technical vision.
Qualifications
Ph.D. or Master's degree in Computer Science, Mathematics, or a related quantitative field. 5+ years of experience in Machine Learning, Deep Learning, or Natural Language Processing. Strong proficiency in Python, CUDA, and GPU acceleration. Deep understanding of Transformer architectures, attention mechanisms, and diffusion models. Proven track record of deploying AI models into high-scale production systems. Excellent problem-solving skills and a passion for ethical AI development.
Responsibilities
- Architect and train state-of-the-art foundation models using PyTorch and TensorFlow.
- Optimize model inference latency and reduce token generation costs for production environments.
- Design and implement Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy.
- Collaborate with product managers to translate business requirements into technical AI solutions.
- Conduct rigorous experimentation and evaluation of model performance using established benchmarks.
- Mentor junior engineers and contribute to the engineering team's technical vision.
Qualifications
- Ph.D. or Master's degree in Computer Science, Mathematics, or a related quantitative field.
- 5+ years of experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Strong proficiency in Python, CUDA, and GPU acceleration.
- Deep understanding of Transformer architectures, attention mechanisms, and diffusion models.
- Proven track record of deploying AI models into high-scale production systems.
- Excellent problem-solving skills and a passion for ethical AI development.