At NVIDIA in Santa Clara, CA, USA, we are currently seeking a skilled AI/ML Infrastructure Engineer to join our team. As an Engineer, you will have a unique chance to enhance productivity for our researchers by implementing improvements throughout the entire stack. Your main responsibility will be to identify and address infrastructure gaps to ensure reliable, efficient, and scalable solutions. Join us and be a part of shaping the future of AI/ML technology!
In this role, you will have the chance to
- Contribute to advanced AI/ML infrastructure solutions that have a direct impact on the efficiency of our highly skilled research teams.
- A dynamic and collaborative environment that values innovation, creativity, and continuous improvement.
- Competitive compensation and comprehensive benefits package.
- Opportunities for professional growth and career advancement within the AI/ML infrastructure domain.
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What you will be doing:
- Work closely with our research teams to comprehend their infrastructure requirements and challenges, translating those observations into actionable enhancements.
- Design and implement solutions for critical areas such as storage management for datasets and logs, error attribution, and core reliability issues within our large scale GPU clusters.
- Continuously monitor and optimize the performance of our AI/ML infrastructure, ensuring high availability, scalability, and efficient resource utilization.
- Create and deploy automation tools, monitoring solutions, and effective operational strategies to simplify infrastructure management and minimize manual tasks.
- Help define and enhance important measures of AI researcher productivity, ensuring that our actions are in line with measurable results.
- Collaborate with diverse teams, including researchers, data engineers, and DevOps professionals, to create a seamless and integrated AI/ML infrastructure ecosystem.
- Keep abreast of the latest advancements in AI/ML infrastructure technologies, frameworks, and effective strategies, and promote their implementation within the company.
What we need to see:
- BS or equivalent experience in Computer Science or related with 3+yrs of relevant experience
- Strong background in software engineering, with experience in building and maintaining large-scale distributed systems, preferably in the context of AI/ML infrastructure.
- Proficiency in programming languages such as Python, Go, or C++, as well as familiarity with cloud computing platforms (e.g., AWS, GCP, Azure).
- Hands-on experience with containerization technologies (e.g., Docker, Kubernetes), automation tools (e.g., Ansible, Terraform), and monitoring solutions (e.g., Prometheus, Grafana).
- Understanding of AI/ML workflows, including data processing, model training, and inference pipelines.
- Excellent problem-solving skills, with the ability to analyze complex systems, identify bottlenecks, and implement scalable solutions.
- Excellent communication and collaboration skills, with the ability to work effectively with diverse teams and individuals.
- Enthusiasm for continual learning and keeping abreast of emerging technologies and effective approaches in the AI/ML infrastructure field.
NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most experienced and versatile people in the world working for us and, due to unprecedented growth, our extraordinary engineering teams are growing fast. If you're a creative and autonomous engineer with real passion for technology, we want to hear from you.
#LI-Hybrid
The base salary range is 120,000 USD - 230,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.