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Mid-level ML role in Bangalore with niche edge/LLM skills reduces candidate density.
Role requires embedded/edge and automotive-focused AI expertise, limiting cross-industry transferability.
Explicit 1–3 year requirement plus mandatory LLM, LangChain, edge deployment, and quantization skills raise filter strictness.
Design and develop LLM-powered agentic AI workflows and multimodal systems specifically for embedded and edge platforms.
Optimize edge AI inferencing using frameworks like TensorFlow Lite, focusing on model quantization and hardware acceleration (NPU/GPU).
Develop scalable microservices architectures and integrate AI agents into distributed systems to enable AI-driven automation and workflow orchestration in automotive embedded systems.
1 to 3 years of experience in AI/ML and software development.
Degree in Computer Science, Information Technology, Communication Technology, or related field.
Hands-on experience with LLM-based application development and agentic AI workflow frameworks such as LangChain.
Experience in edge AI deployment including TensorFlow Lite or similar frameworks, model optimization, quantization, and understanding of hardware acceleration (NPU/GPU).
Practical experience building AI agents and orchestration pipelines in production embedded/edge environments, prioritizing real-time inferencing.
Familiarity with microservices architecture and distributed systems for scalable AI deployments in automotive or related domains.
Strategic focus on integrating AI-driven automation into software development lifecycle processes like defect analysis, requirement processing, or workflow automation.