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 robust 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

- Experience: 5+ years in Validation, QA Automation, Embedded Systems, or AI Platform Testing.
- Programming: Python, Bash, C/C++; Linux, Embedded Linux, Shell Scripting.
- Automation & DevOps: Jenkins/GitHub Actions, Docker, Git, CI/CD.
- Validation: Functional, Regression, System, AI/ML Model Validation, Performance Benchmarking, Stress & Reliability Testing.
- AI/Embedded: OpenCV, TensorFlow, PyTorch, ONNX; Edge AI, LLM/VLM validation (preferred).
- Hardware Validation: PCIe, USB, Networking, Kernel Drivers, Hardware-Software Integration.
- Tools: Jira, Confluence, Redis.
- Preferred: Experience in AI accelerators/Semiconductor companies, compiler/runtime validation, inference frameworks, and distributed automation.

📌 Validation Engineers (Hyderabad)
🏢 Kinara.ai
📍 Hyderabad