1 day ago
Santa Clara, CA, USAMid Level
H1B sponsor
Base Salary
$152k - $242k/yr
Responsibilities
- Architect, deploy, and scale open-source models using Kubernetes, Ray, Slurm, or comparable distributed orchestration frameworks.
- Design machine learning systems and data pipelines, and prompt-tune, evaluate, benchmark, and deploy production-grade models and AI agents.
- Perform model error and gap analysis and build analytics dashboards to communicate performance findings.
- Own features from ideation through production, including architectural decisions, repository coordination, and community interactions.
- Optimize GPU memory usage and infrastructure for high-throughput, low-latency inference across multi-node clusters.
- Build GitLab CI/CD pipelines with automated testing and vulnerability scanners integrated into merge-request workflows.
- Develop automated testing frameworks and test-generation workflows for AI systems.
- Manage advanced Git workflows, including rebasing, cryptographic commit signing, and public/private repository mirroring.
Requirements
- Master’s or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
- At least 3 years of professional experience writing production-grade asynchronous Python.
- Deep experience with LangChain, Hugging Face libraries, vLLM, and SGLang.
- Experience with TensorFlow, PyTorch, and Scikit-learn.
- Proficiency in Python-based data analysis using pandas, NumPy, or similar tools.
- Hands-on experience deploying, monitoring, analyzing, and scaling models with Kubernetes, Ray, or Slurm in multi-node environments.
- Strong understanding of GPU memory management and infrastructure-level tuning for AI inference.
- Advanced knowledge of GitLab pipelines, automated test jobs, and vulnerability-scanner integration.
- Expert familiarity with Python testing frameworks such as PyTest, mocking libraries, and automated test-generation frameworks.
- High proficiency with advanced Git workflows, including rebase strategies, cryptographic commit signing, and repository mirroring.
- Experience aligning or fine-tuning LLMs, VLMs, or any-to-text models is a preferred qualification.
- Research experience, scientific publications, and demonstrated interest in advancing AI are preferred qualifications.
Benefits
- Eligible for equity and a comprehensive benefits package.
- The posting states that applications will be accepted at least until September 12, 2026.
- This is an existing vacancy.
Tech Stack
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.