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Tier-1 brand and popular AI role, but specialized agentic/edge skillset limits applicant pool.
Medium: core ML skills transferable, but embedded edge and hardware specialization increases domain specificity.
High due to explicit 1–3 years plus mandatory LLM, edge deployment, and hardware acceleration experience.
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Design and develop LLM-powered agentic AI workflows for embedded and edge platforms, focusing on autonomous AI workflows and real-time inferencing.
Build and optimize multimodal AI systems, including RAG pipelines, prompt engineering, and edge AI deployment using TensorFlow Lite or similar frameworks with hardware acceleration (NPU/GPU).
Develop microservices-based AI architectures and integrate AI agents into distributed and service-oriented systems, collaborating with cross-functional teams to automate software development and validation workflows.
1 to 3 years of experience in AI/ML and software development with hands-on experience in LLM-based applications and agentic AI orchestration frameworks (e.g., LangChain).
Degree in Computer Science, Information Technology, Communication Technology, or related field.
Experience with edge AI deployment including TensorFlow Lite, model optimization/quantization, and knowledge of hardware acceleration (NPU/GPU).
Work Experience Required: 1 to 3 years in AI/ML and software development; Mandate to work 5 days a week in office.
Candidate with strong expertise in building LLM-powered AI workflows and multimodal AI systems tailored for embedded/edge environments.
Experience or interest in microservices and distributed systems design for scalable AI deployment in automotive or embedded contexts.
Familiarity with integrating AI-driven automation into software development lifecycle and validation processes, preferably in fast-paced and innovation-driven environments.