Job Description
Are You Ready to Architect the Future of Intelligence?
Nexus AI Solutions is at the forefront of the generative AI revolution. We are looking for a visionary Senior AI Engineer to join our elite engineering team in Mountain View. In this role, you won't just use existing models; you will build, optimize, and deploy next-generation deep learning architectures that redefine user experiences.
You will work in a dynamic, collaborative environment alongside top-tier researchers and data scientists. If you are passionate about pushing the boundaries of Large Language Models (LLMs), scaling AI infrastructure, and solving complex problems with elegant code, we want to hear from you.
Why Join Us?
- Impactful Work: Your code will power the AI experiences of millions of users.
- Top-Tier Compensation: Competitive salary, equity, and comprehensive benefits.
- Cutting-Edge Tech Stack: Work with PyTorch, TensorFlow, and modern cloud infrastructure.
- Remote-First Culture: Flexible work arrangements with a focus on results.
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art deep learning models, specifically focusing on NLP and generative AI applications.
- System Optimization: Optimize inference latency and throughput for production-scale models using techniques like quantization, pruning, and distillation.
- MLOps Implementation: Build and maintain robust CI/CD pipelines for model deployment, ensuring high availability and automated retraining workflows.
- Research & Innovation: Stay ahead of the curve by implementing the latest research findings and contributing to our internal open-source library.
- Collaboration: Partner with product managers and engineers to translate complex AI capabilities into user-friendly features.
- Performance Monitoring: Establish rigorous monitoring and alerting systems to track model performance and data drift in real-time.
Qualifications
- Education: BS, MS, or PhD in Computer Science, Mathematics, or a related field.
- Experience: 5+ years of professional experience in machine learning, deep learning, or artificial intelligence engineering.
- Technical Proficiency: Strong proficiency in Python, PyTorch, and TensorFlow.
- Architecture: Deep understanding of neural network architectures, transformers, and attention mechanisms.
- Cloud Expertise: Experience deploying models on cloud platforms (AWS, GCP, or Azure).
- Problem Solving: Ability to debug complex distributed systems and optimize resource utilization.