Job Description
Are you ready to shape the future of Artificial Intelligence? Nexus AI is seeking a visionary Senior AI Engineer to join our elite engineering team in San Francisco. In this role, you will architect and deploy state-of-the-art Large Language Models (LLMs) that redefine how users interact with technology.
We are a fast-paced, forward-thinking company focused on solving complex problems with data-driven solutions. If you have a passion for machine learning, deep learning, and scalable software architecture, we want to hear from you.
What You Will Do
Our team is pushing the boundaries of what's possible with AI. Your day-to-day will involve:
- Model Development: Design, train, and fine-tune deep learning models using PyTorch and TensorFlow.
- Production Deployment: Move models from research to production, ensuring high availability and low latency.
- Optimization: Implement inference optimization techniques (quantization, pruning, distillation) to handle massive scale.
- Collaboration: Work closely with data scientists, product managers, and backend engineers to align AI capabilities with business goals.
- Mentorship: Guide junior engineers and conduct rigorous code reviews to maintain high technical standards.
Who You Are
We are looking for a seasoned professional who thrives in a dynamic environment. The ideal candidate possesses:
- Education: Master’s or Ph.D. in Computer Science, Mathematics, or a related technical field.
- Experience: 5+ years of experience in Machine Learning, Deep Learning, or Natural Language Processing (NLP).
- Technical Skills: Proficiency in Python, PyTorch, and Hugging Face Transformers. Strong understanding of Transformer architectures.
- Infrastructure: Experience deploying models on cloud platforms (AWS, GCP, or Azure) using Kubernetes or Docker.
- Problem Solving: Ability to tackle ambiguous problems and derive data-driven insights.
Responsibilities
- Architect and implement scalable machine learning pipelines.
- Research and integrate cutting-edge AI methodologies into production systems.
- Optimize neural networks for speed and memory efficiency.
- Ensure data privacy, security, and compliance in AI model deployment.
- Document technical architecture and model performance metrics.
- Contribute to the open-source community and internal engineering blogs.
Qualifications
- Master’s degree or higher in Computer Science, AI, or a related field.
- Extensive experience with Python, PyTorch, and TensorFlow.
- Deep knowledge of LLMs, NLP, and Generative AI models.
- Experience with cloud services (AWS/GCP) and containerization (Docker/K8s).
- Strong grasp of statistics and mathematical modeling.
- Excellent verbal and written communication skills.