About this role
Apply for AI/ML Engineer – LLM & Voice Pipeline in Remote India
Project description
Our client is advancing its in-vehicle voice assistant into an intelligent, AI-powered companion. Since 2024, they have been incorporating large-language-model capabilities (Azure OpenAI / ChatGPT) into vehicles equipped with the MIB3 infotainment system, with new E³-architecture models featuring enhanced voice functions from the factory. The AIME (AI Model Engine) backend program supports this development over a multi-year timeline, addressing natural-language dialogue, empathic communication, and the complete cloud-edge data pipeline. DXC Luxoft serves as the end-to-end delivery partner, collaborating closely with the client’s engineers within a joint product team on the Azure platform (AKS, Azure OpenAI, Managed Identity, Azure Monitor, Azure DevOps).
Responsibilities
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Design, implement, and optimize RAG pipelines integrating Azure AI Search, vector stores, and LLM completion endpoints.
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Develop and maintain ASR and TTS integration modules, including audio pre
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and post-processing using pyAudio and librosa.
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Create LLM prompt chains, evaluation frameworks, and safety/alignment guardrails for in-vehicle dialogue scenarios.
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Prototype AI capabilities such as few-shot adapters, intent classification, and empathic dialogue, then transition prototypes to production.
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Collaborate with Backend Engineers to develop the FastAPI/Kafka interface connecting the AI layer with the streaming infrastructure.
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Contribute to edge AI components including on-device inference, model quantization, and latency management for in-vehicle use.
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Monitor and enhance model quality metrics including BLEU, WER, CER, and faithfulness via continuous evaluation pipelines.
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Participate in code reviews with cross-functional teams, including customer ML engineers.
Skills
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Must have
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3+ years of hands-on AI/ML engineering in production environments.
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Strong Python skills; experience with LLM frameworks: LangChain, LangGraph, or equivalent.
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Practical experience building RAG systems (chunking strategies, embedding models, retrieval evaluation).
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Familiarity with Azure OpenAI Service or OpenAI API; prompt engineering best practices.
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Experience with at least one ASR engine (Whisper, Azure Speech, or equivalent) and a TTS system.
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English B2 or above.
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Nice to have
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pyAudio / librosa audio signal processing.
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Edge inference: ONNX, TensorRT, or on-device model deployment.
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Automotive in-vehicle speech processing context (noise cancellation, far-field microphones).
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Experience with LLM evaluation frameworks (DeepEval, Ragas, PromptFlow).
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German language skills.
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Other
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Languages
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English: B2 Upper Intermediate
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Seniority
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Senior
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Remote India, India
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Req. VR-125479
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AI/ML
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Automotive Industry
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12/10/2026
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Req. VR-125479