Job Description
Are you ready to define the future of intelligent systems?
Nexus AI Systems is seeking a visionary Senior AI Engineer to join our elite engineering team in San Francisco. We are building the next generation of autonomous agents and generative AI solutions, and we need a technical leader to architect scalable, robust, and ethical models.
In this high-impact role, you will bridge the gap between theoretical research and production-ready software. You will work alongside world-class data scientists and researchers to deploy models that power enterprise-grade applications globally.
Nexus AI Systems is seeking a visionary Senior AI Engineer to join our elite engineering team in San Francisco. We are building the next generation of autonomous agents and generative AI solutions, and we need a technical leader to architect scalable, robust, and ethical models.
In this high-impact role, you will bridge the gap between theoretical research and production-ready software. You will work alongside world-class data scientists and researchers to deploy models that power enterprise-grade applications globally.
Responsibilities
- Architecture & Design: Design and implement scalable machine learning pipelines and AI system architectures capable of handling millions of transactions.
- Model Development: Lead the research, training, fine-tuning, and deployment of Large Language Models (LLMs) and computer vision models.
- Optimization: Optimize model inference speed and reduce latency using techniques such as quantization and model distillation.
- Collaboration: Partner with product managers and software engineers to integrate AI models seamlessly into web and mobile applications.
- Mentorship: Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
Qualifications
- Education: Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related technical field (Master’s degree preferred).
- Experience: 5+ years of professional experience in software engineering or machine learning engineering.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Deep understanding of deep learning architectures and NLP.
- Cloud Mastery: Extensive experience deploying models on AWS, GCP, or Azure using containerization (Docker, Kubernetes).
- Problem Solving: Exceptional ability to debug complex system issues and optimize performance bottlenecks.