Member of Technical Staff, Cloud Infrastructure
Build and optimize backend infrastructure that powers high-performance generative AI workloads. The role requires experience scaling enterprise machine-learning systems and working with ML infrastructure such as PyTorch, Vertex AI, or SageMaker.
About the job
Responsibilities
- Design and build core backend software components, ensuring efficiency, scalability, and stability of system resources.
- Conduct design and code reviews and collaborate with cross-functional teams.
- Continuously analyze and optimize infrastructure efficiency for AI workloads, including compute, storage, and networking.
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
- 3+ years of experience working in machine learning infrastructure, such as PyTorch, Vertex AI, or SageMaker.
- Experience building, scaling, and optimizing enterprise-grade machine learning systems.
Nice-to-Haves
- Experience in AI or large-scale infrastructure.
- Master’s or PhD degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
Benefits
- Solve challenging problems at the forefront of AI infrastructure, including low-latency inference and scalable model serving.
- Work with emerging technology that shapes how businesses and developers use AI.
- High ownership and direct impact in a fast-growing team.
- Collaborate with experienced engineers and AI researchers.
Skills
Machine Learning Infrastructure, PyTorch, Google Vertex Ai, Amazon Sagemaker, Artificial Intelligence, Machine Learning Systems, Backend Software, Cloud Infrastructure, Compute, Storage, Networking, Model Serving
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