Job Description
Are you ready to define the standard for artificial intelligence in the next era? At Vertex AI Solutions, we aren't just building models; we are architecting the future. We are seeking a visionary Senior AI Engineer to lead our initiatives in developing cutting-edge generative models and scalable machine learning infrastructure.
In this pivotal role, you will bridge the gap between theoretical research and production-grade deployment. You will work in a dynamic, high-performance environment where your code directly impacts millions of users. If you are passionate about the next generation of AI and want to build the technology that defines 2026, we want to hear from you.
Why Join Us?
- Work with state-of-the-art hardware and cloud infrastructure.
- Competitive compensation and equity packages.
- Flexible remote-first culture with a vibrant San Francisco office.
- Opportunity to mentor junior engineers and shape engineering standards.
Responsibilities
- Model Architecture & Development: Design, train, and fine-tune advanced neural network architectures, including Large Language Models (LLMs) and multimodal systems.
- Production Deployment: Implement and optimize MLOps pipelines using tools like Kubernetes, Docker, and TensorFlow Serving to ensure high availability and low latency.
- Research & Innovation: Stay at the forefront of AI research, implementing novel techniques to improve model accuracy, efficiency, and fairness.
- Code Quality: Write clean, maintainable, and scalable Python code, conducting thorough code reviews and establishing engineering best practices.
- Collaboration: Partner with product managers, data scientists, and designers to translate business requirements into technical AI solutions.
- Performance Optimization: Analyze and optimize model inference times and resource utilization to reduce operational costs.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Mathematics, or a related technical field.
- Experience: Minimum of 5 years of professional experience in machine learning engineering or AI research.
- Programming: Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
- Infrastructure: Deep understanding of cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Mathematics: Solid foundation in linear algebra, calculus, probability, and statistics.
- Problem Solving: Demonstrated ability to troubleshoot complex system issues and optimize performance under tight deadlines.