Edge AI Engineer

You will be joining Senzcraft, a hyper-automation company founded by IIM Bangalore and IEST Shibpur alumni with the vision to Radically Simplify Today's Work and Design Business Process For The Future. Senzcraft has a suite of SaaS products and services and partners with automation product companies, being awarded by Analytics India Magazine as a "Niche AI startup" and recognized by NY-based SSON as a top hyper-automation solutions provider. As an engineer at Senzcraft, your role will involve deploying and optimizing Large Language Models (LLMs) on edge devices, particularly NVIDIA Jetson platforms. Beyond model inference, you will design practical LLM-based solutions for real-world scenarios using prompt engineering, input preprocessing, caching strategies, data creation, and model fine-tuning as needed. You should possess the skills to make LLM applications reliable, efficient, and context-aware within edge-device constraints like limited compute, memory, latency, and power. Key Responsibilities: - Hands-on experience with LLMs, prompt engineering, and scenario-specific prompt design. - Experience running AI/ML models on edge devices with compute and memory constraints. - Practical knowledge of preprocessing techniques for text, speech transcripts, and structured inputs. - Implementation of caching, context management, and optimization techniques for LLM applications. - Ability to create datasets and fine-tune or adapt models for domain-specific use cases. - Strong proficiency in Python programming. - Understanding of NLP tasks such as intent handling, entity extraction, and text classification. - Experience with model evaluation, latency optimization, and debugging AI behavior. - Familiarity with NVIDIA Jetson or similar edge AI platforms. Qualifications Required: - Experience with speech processing, speech-to-text systems, and audio preprocessing is a plus. - Knowledge of noise handling, speech enhancement, and robust voice input pipelines is beneficial. - Experience with NER models and entity extraction pipelines. - Familiarity with TensorRT, ONNX, PyTorch, Hugging Face, or similar model deployment tools. - Experience with quantization, pruning, distillation, or other model compression techniques. - Knowledge of retrieval-augmented generation, vector databases, or local knowledge caching. - Experience building real-time AI applications on embedded Linux systems. - Familiarity with multilingual or domain-specific language processing. - Experience integrating LLMs with sensors, robotics, industrial systems, or IoT devices. This role is based in Bangalore on a hybrid work model and requires 4-6 years of experience in the field. You will be joining Senzcraft, a hyper-automation company founded by IIM Bangalore and IEST Shibpur alumni with the vision to Radically Simplify Today's Work and Design Business Process For The Future. Senzcraft has a suite of SaaS products and services and partners with automation product companies, being awarded by Analytics India Magazine as a "Niche AI startup" and recognized by NY-based SSON as a top hyper-automation solutions provider. As an engineer at Senzcraft, your role will involve deploying and optimizing Large Language Models (LLMs) on edge devices, particularly NVIDIA Jetson platforms. Beyond model inference, you will design practical LLM-based solutions for real-world scenarios using prompt engineering, input preprocessing, caching strategies, data creation, and model fine-tuning as needed. You should possess the skills to make LLM applications reliable, efficient, and context-aware within edge-device constraints like limited compute, memory, latency, and power. Key Responsibilities: - Hands-on experience with LLMs, prompt engineering, and scenario-specific prompt design. - Experience running AI/ML models on edge devices with compute and memory constraints. - Practical knowledge of preprocessing techniques for text, speech transcripts, and structured inputs. - Implementation of caching, context management, and optimization techniques for LLM applications. - Ability to create datasets and fine-tune or adapt models for domain-specific use cases. - Strong proficiency in Python programming. - Understanding of NLP tasks such as intent handling, entity extraction, and text classification. - Experience with model evaluation, latency optimization, and debugging AI behavior. - Familiarity with NVIDIA Jetson or similar edge AI platforms. Qualifications Required: - Experience with speech processing, speech-to-text systems, and audio preprocessing is a plus. - Knowledge of noise handling, speech enhancement, and robust voice input pipelines is beneficial. - Experience with NER models and entity extraction pipelines. - Familiarity with TensorRT, ONNX, PyTorch, Hugging Face, or similar model deployment tools. - Experience with quantization, pruning, distillation, or other model compression techniques. - Knowledge of retrieval-augmented generation, vector databases, or local