Used Tools & Technologies
Machine LearningRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Software Development @ 7
Docker @ 4
Kubernetes @ 4
Linux @ 4
Python @ 7
CI/CD @ 4
Distributed Systems @ 4
Leadership @ 7
Communication @ 4
Microservices @ 4
Debugging @ 7
API @ 4
Technical Leadership @ 7
LLM @ 4
AI @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA is the world leader in accelerated computing and AI. Our technologies power the most advanced AI platforms, including NeMo microservices and NVIDIA Inference Microservices (NIM), enabling scalable, production-grade AI deployment across cloud and enterprise environments. We are looking for a senior, technically strong test development engineer to drive quality, automation, and technical leadership in this rapidly evolving space.
Responsibilities
- Own and drive end-to-end quality from design through release and production readiness
- Lead test strategy, planning, and execution across functional, integration, system, performance, and reliability testing
- Design, build, and maintain test frameworks and automation for microservice-based, containerized AI systems
- Provide technical leadership and mentorship to less senior engineers, guiding test design, automation practices, and quality standards
- Partner closely with cross-functional teams to influence architecture and improve testability
- Validate LLM and AI inference workflows, including model lifecycle, APIs, CLIs, deployment configurations, and scaling scenarios
- Drive defect triage, root-cause analysis, and quality metrics, ensuring issues are addressed systematically and efficiently
- Leverage AI-assisted testing techniques to improve coverage, efficiency, and signal-to-noise in test results
Requirements
- BS or higher degree in CS/EE/CE majors (or equivalent experience)
- 8+ years of experience in software development, test development, or quality engineering roles
- Strong proficiency in Python and test automation frameworks
- Experience testing distributed systems, microservices, or cloud-native platforms
- Solid understanding of Linux, Docker, Kubernetes, and CI/CD pipelines
- Proven ability to lead technically, review designs, and mentor other engineers
- Strong debugging skills and ability to reason about complex, system-level failures
- Excellent communication skills and experience working across geographically distributed teams
Ways to Stand Out
- Experience testing AI/ML platforms, LLM pipelines, or inference services
- Hands-on exposure to NeMo, NIM, or model-as-a-service platforms
- Experience with performance, scale, and reliability testing in production-like environments
- Applying AI tools to enhance test development, automation, and diagnostics
- Prior ownership of quality for customer-facing or production-critical services
Compensation and Benefits
- Base salary ranges (depending on level and location):
- Level 4: 168,000 USD - 270,250 USD
- Level 5: 200,000 USD - 322,000 USD
- Eligible for equity and company benefits
Applications for this job will be accepted at least until March 24, 2026. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer.