Role Summary
- Work closely with technical marketing, product, and customer support teams in understanding the benchmark data requirements. Explore various bench marking methods , tools used in vision,LLM/VLM models and adopt the same to evaluate Kinara products
- Writing and optimizing scripts for deep learning model deployment and benchmarking. Preparing detailed benchmarking and analysis reports for engineering and marketing stakeholders.
Job Responsibility
- Proficiency in Python (for AI workload scripting/optimization), C or C++ (for low-level performance work).
- Familiarity with AI accelerators, LLM frameworks, and inference servers.
- Measuring and reporting on latency, throughput, accuracy, and power consumption of AI workloads.
- Familiarity with MLPerf and MLFlow bench marking suites for computer vision models
- Familiarity with various LLM bench mark methods like MMLU, HumanEval, GSM8K, ARC Challenge, GPQA..etc
- Working knowledge of Linux environments and device driver internals is often preferred.
- Familiarity with CI/CD tools, version control (GitHub), and automation frameworks.
Job Qualification
- BTech in ECE/CS 4+ years of experience, Machine Learning, or a related field.
- Exposure to Neural Networks, AI/ML/DL models, training, and frameworks like TensorFlow, Caffe, and PyTorch.
- Experience in developing AI workload flows in C++ and Python
- Experience in performance evaluation of hardware and software systems.
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