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описание
Grid Dynamics is a technology consulting, platform, and product engineering company that provides AI and advanced analytics services to enterprise clients undergoing digital transformation.
задачи
Evaluate results from automated benchmarking suites to detect and analyze performance shifts and metrics;
Perform deep-dive root-cause analysis on bisection results to identify code changes responsible for performance regressions;
Develop and maintain Python-based tooling for benchmark automation, hardware configuration management, and automated data recovery;
Troubleshoot failures within the benchmarking pipeline, including script errors, environment misconfigurations, and resource allocation issues in distributed clusters;
Maintain and enhance data pipelines and visualization tools to ensure high-fidelity performance metrics are available for engineering teams;
Develop and maintain engineering playbooks and best practices to improve consistency in performance testing and incident investigation.
требования
Strong proficiency in Python for systems automation, data processing, and integration;
Hands-on experience with SQL for querying large datasets and managing performance metrics;
Deep knowledge of Linux/Unix environments, shell scripting (Bash), and command-line development;
Exceptional analytical and problem-solving skills with the ability to debug complex system-level issues;
Clear written communication skills for documenting technical investigations and collaborating across globally distributed teams;
Nice to have: practical experience with distributed build and test systems (e.g., Bazel, CMake), strong familiarity with CI/CD pipelines and automated regression testing, basic understanding of hardware accelerators (GPUs) or machine learning frameworks (JAX, PyTorch, TensorFlow), background in Performance Engineering or SRE.