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Tier-1 brand plus mid-level generalist title and common DevOps skills raise applicant competition.
AI inference and automation specifics moderately constrain transferability across non-AI industries.
Explicit 5+ years requirement and mandatory tech stack (CI/CD, languages, databases, Kubernetes) enforce strict filters.
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Design, implement, and maintain infrastructure for running AI workloads through various inference backends such as Llama.cpp, Ollama, Pytorch, WinML, TRT-RTX.
Develop solutions to deploy AI applications and models in automation, including measuring accuracy, functionality, and performance.
Build and maintain automated systems like CI/CD pipelines, local model repositories, and data processing engines to support Local AI automation.
5+ years of experience with a B.Tech or higher degree in Computer Science, IT, Software Engineering, or related field.
5+ years of application development experience in C#, Java, or another programming language, plus exposure to at least one scripting language (Python, Perl, or PHP).
Experience with databases, SQL, source control systems (Git, Perforce), and CI/CD pipelines (Jenkins).
Outstanding written and oral communication skills for collaboration with management and engineering teams.
Experienced in building robust backend automation systems with practical database management skills.
Familiarity with visualization tools such as Grafana or Kibana for designing interfaces.
Hands-on experience managing Git CI/CD pipelines, Kubernetes, Docker, and inference frameworks like Llama.cpp, Ollama, and Pytorch.