Job Summary
We are looking for a Validation Engineer to validate and qualify AI software, firmware, hardware, and system-level features for edge AI accelerator platforms. The role involves designing validation strategies, developing automation frameworks, executing functional and performance testing, and ensuring high-quality releases across embedded and AI workloads.
The ideal candidate should have strong experience in Linux systems, automation, AI/ML validation, CI/CD workflows, and debugging complex hardware-software interactions.
Key Responsibilities
Design and execute validation plans for AI accelerator platforms, embedded systems, and SDK releases.
Validate AI/ML workloads including LLMs, VLMs, vision, audio, and NLP models across different hardware targets.
Develop and maintain automation frameworks using Python, Bash, Jenkins, and CI/CD pipelines.
Perform functional, regression, stress, performance, and scalability testing.
Validate PCIe, USB, networking, memory, storage, and system-level interfaces.
Debug issues across firmware, kernel drivers, runtime, and application layers.
Work closely with software, compiler, runtime, hardware, and DevOps teams for issue triaging and release qualification.
Build automated validation pipelines for nightly, release, and PR-based testing.
Analyze logs, crashes, performance bottlenecks, and system stability issues.
Create detailed validation reports, dashboards, and quality metrics.
Support customer-specific validation and benchmarking activities.
Manage and maintain lab infrastructure, devices, and automated execution environments.
Validate deployments across x86, ARM, Linux, containerized, and cloud-based environments.
Ensure release readiness through comprehensive test coverage and execution.
Required Skills
Technical Skills
Strong experience in:
Python scripting and automation
Linux systems and shell scripting
CI/CD tools such as Jenkins/GitHub Actions
Docker and containerized environments
Git version control
Embedded Linux systems
Debugging and log analysis
Validation Expertise
Experience with:
Functional and regression testing
System validation
AI/ML model validation
Performance benchmarking
Stress and reliability testing
Automation framework development
Preferred Areas
AI accelerator or semiconductor validation
Edge AI platforms
LLM/VLM validation
OpenCV, TensorFlow, PyTorch, ONNX
PCIe, USB, networking, and kernel driver validation
Docker, Git
Hardware-software integration testing
Qualifications
Bachelor’s or Master’s degree in:
Computer Science
Electronics & Communication
Electrical Engineering
Embedded Systems
Related field
5+ years of experience in validation, QA automation, embedded systems, or AI platform testing.
Good to Have
Experience in semiconductor or AI hardware companies.
Exposure to performance profiling and benchmarking tools.
Experience with distributed systems and large-scale automation.
Knowledge of compiler/runtime validation.
Familiarity with model deployment pipelines and inference frameworks.
Soft Skills
Strong debugging and analytical skills
Excellent communication and collaboration
Ability to work in fast-paced product environments
Ownership mindset and problem-solving attitude
Ability to coordinate across multiple engineering teams
Example Tools & Technologies
Python, Bash, C/C++
Jenkins, Docker, Git
Linux, Ubuntu, Embedded Linux
PyTorch, TensorFlow
Redis
Jira, Confluence
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