Job Description
We are building the operating system for the 2026 era. Nexus Dynamics is seeking a visionary Lead AI Architect to spearhead our next-generation autonomous systems. You will define the technical roadmap for our AGI readiness initiatives, bridging the gap between theoretical machine learning breakthroughs and scalable production infrastructure. If you are passionate about shaping the future of human-AI interaction and want to lead a team of elite engineers in San Francisco, apply today.
Responsibilities
- Architect 2026 Roadmap: Design and implement the core infrastructure for our next-generation Generative AI models, focusing on efficiency and scalability.
- Model Optimization: Oversee the deployment of Large Language Models (LLMs) and Multi-modal AI systems, ensuring low-latency inference in real-world environments.
- Team Leadership: Mentor a high-performance team of ML Engineers and Data Scientists, fostering a culture of innovation and technical excellence.
- Cross-Functional Collaboration: Partner with product managers and researchers to translate complex AI capabilities into user-centric features.
- MLOps Strategy: Build robust CI/CD pipelines and infrastructure to automate model training, validation, and deployment.
- Future Tech Research: Stay at the forefront of emerging technologies (Quantum Computing, Edge AI) and evaluate their integration into our 2026 product suite.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 8+ years of experience in software engineering, with at least 4 years specifically in Machine Learning and Deep Learning architecture.
- Technical Skills: Expert proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (Kubernetes, Docker).
- AI Expertise: Deep understanding of NLP, Computer Vision, and Reinforcement Learning; experience with state-of-the-art LLMs (GPT-4, Claude, Llama).
- Leadership: Proven track record of leading engineering teams and delivering complex technical projects on time.
- Problem Solving: Exceptional ability to troubleshoot complex system bottlenecks and optimize large-scale data pipelines.