Job Description
We are not just predicting the future; we are building it. Nexus AI Labs is seeking a visionary Lead AI Engineer to spearhead the development of the artificial intelligence systems that will define 2026. You will work at the intersection of research and engineering to build scalable, high-performance neural networks.
In this high-impact role, you will lead a team of talented engineers in deploying state-of-the-art Large Language Models (LLMs) and generative AI solutions. We value innovation, autonomy, and the pursuit of excellence.
Key Benefits:
- Competitive base salary and equity stake in a unicorn startup.
- Full remote flexibility or hybrid work in our SF hub.
- Access to top-tier compute resources for research.
- Professional development budget for conferences and courses.
Responsibilities
- Model Development: Design and implement robust deep learning architectures, specifically focusing on Transformers and RAG (Retrieval-Augmented Generation) systems.
- Training Pipelines: Oversee the full lifecycle of model training, including data preprocessing, hyperparameter tuning, and distributed training strategies.
- Optimization: Engineer solutions to reduce inference latency and computational costs, ensuring models run efficiently in production environments.
- Infrastructure: Build and maintain MLOps pipelines using Docker, Kubernetes, and cloud services (AWS/GCP) to ensure model reliability and scalability.
- Research: Stay ahead of the curve by integrating the latest academic research into our production codebase.
- Leadership: Mentor junior engineers and conduct technical code reviews to maintain high engineering standards.
Qualifications
- Education: MS or PhD in Computer Science, Statistics, or a related technical field.
- Experience: 5+ years of professional experience in machine learning engineering or applied AI research.
- Programming: Deep proficiency in Python and frameworks such as PyTorch or TensorFlow.
- Cloud & Tools: Extensive experience with cloud platforms (AWS/GCP/Azure) and CI/CD tools.
- Soft Skills: Exceptional problem-solving abilities and the ability to communicate complex technical concepts to non-technical stakeholders.