Job Description
About Nexus Future Systems
We are the architects of tomorrow, building the infrastructure that powers the next generation of intelligent applications. As a leader in the AI space, we are looking for a visionary Senior AI Engineer to join our elite team in San Francisco. If you are passionate about pushing the boundaries of what is possible with Large Language Models (LLMs) and Generative AI, this is your opportunity to shape the future.
The Role
We are seeking a Senior AI Engineer to design, train, and deploy state-of-the-art machine learning models. You will work at the intersection of research and engineering, ensuring our AI systems are scalable, efficient, and capable of solving complex real-world problems.
Why Join Us?
- Work with cutting-edge AI technologies and frameworks.
- Competitive compensation and equity package.
- Flexible remote and hybrid work options.
- Professional development and continuous learning opportunities.
Responsibilities
- Model Development: Design, train, and fine-tune large-scale transformer models and generative AI architectures.
- System Optimization: Optimize model inference latency and throughput for high-traffic production environments.
- Infrastructure: Build and maintain robust MLOps pipelines using tools like Docker, Kubernetes, and cloud platforms (AWS/GCP).
- Collaboration: Partner with cross-functional teams of data scientists, product managers, and software engineers.
- Research: Stay current with the latest advancements in AI research and implement novel techniques.
- Deployment: Ensure reliable deployment of models with rigorous monitoring and error handling.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in AI/ML engineering, with a focus on Deep Learning and NLP.
- Technical Skills: Proficiency in Python, PyTorch or TensorFlow, and SQL.
- Modeling: Strong experience with LLMs, RAG (Retrieval-Augmented Generation), and prompt engineering.
- DevOps: Experience with MLOps tools, version control (Git), and CI/CD pipelines.
- Communication: Excellent verbal and written communication skills for technical and non-technical audiences.