16 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Define and own end-to-end validation strategy for the AI software stack, including methodologies, coverage metrics, quality gates, and release-readiness criteria.
- Lead validation of neural-network operators, compute kernels, graph-level execution, end-to-end model inference, and software behavior across hardware revisions.
- Validate memory allocation and movement across host and device environments, including stress, concurrency, and multi-device scenarios.
- Design and maintain benchmarking frameworks for operator performance, model performance, latency, throughput, time-to-first-token or result, and multi-device scaling efficiency.
- Mentor engineers and drive automation, performance-validation, debugging, and software-quality best practices.
- Lead cross-functional validation efforts with compiler, runtime, kernel, and hardware teams.
Requirements
- 10+ years of experience in AI software validation, systems software validation, performance engineering, or related areas.
- Strong C++ software development expertise and object-oriented programming fundamentals.
- Advanced Python programming skills for automation and test infrastructure.
- Deep understanding of AI/ML execution pipelines, neural-network operators, deep-learning frameworks, runtime architectures, scheduling systems, parallel execution models, memory hierarchy, and DMA concepts.
- Experience validating large-scale AI workloads and inference systems.
- Proven experience building automated test and benchmarking frameworks, with strong debugging and root-cause analysis skills.
- Preferred: experience with MLIR, XLA, StableHLO, TVM, ONNX Runtime, TensorRT, or similar compiler/runtime stacks.
- Preferred: experience validating GPU, NPU, FPGA, or custom accelerator platforms.
- Preferred: hands-on experience with VTune, Nsight Systems, Nsight Compute, perf, or gprof.
- Preferred: experience with distributed inference and multi-device execution, familiarity with LLM, multimodal, and generative AI workloads, and experience leading software quality or validation teams.