AI/ML Engineer

• Design, train, and optimize AI/ML models for real-time, edge-based deployment.
• Design, implement, and optimize Retrieval-Augmented Generation (RAG) workflows and fine-tune large language models (LLMs) to build scalable, secure, and production-ready enterprise GenAI applications.
• Work with multi-modal data sources (audio, vision, sensor, telematics) to build robust AI systems.
• Develop end-to-end pipelines for data preprocessing, model training, evaluation, and deployment.
• Implement algorithms optimized for embedded and resource-constrained platforms
• Validate AI models with real-world automotive datasets.
• Perform model optimization (quantization, pruning) for deployment on embedded SoCs
• Collaborate with system architects, Application developers, and automotive domain experts to ensure end-to-end functionality
• Stay up to date with AI/ML advancements and automotive industry trends.

Work Experience

Required Skills (Technical Competency):

• 4–5 years of proven development experience in AI/ML for embedded device
• Strong expertise in deep learning frameworks (TensorFlow, PyTorch, ONNX, TensorRT).
• Expert proficiency with open-source infrastructure tools like llama.cpp, vLLM, Ollama, and NVIDIA Triton Inference Server for local model serving, high-throughput inference, and quantization.
• Hands-on experience building complex, stateful workflows and tracking applications using LangChain, LangGraph, and Langfuse.
• Expertise in selecting, benchmarking, and adapting state-of-the-art open-source architectures (such as Llama 3, gemma, Qwen, and Kimi) for enterprise tasks
• Practical experience with edge/embedded AI (NVIDIA Jetson, Qualcomm, ARM).
• Proficiency in NLP / Conversational AI / Speech interfaces ( ASR, TTS )
• Solid programming skills in Python and C++/Java for optimization and integration.
• Solid understanding of application development in embedded Linux / Android
• Familiarity with automotive standards, protocols such as CAN
• Familiarity with cloud ML services like AWS SageMaker or Azure ML
• Good communication skills and great team spirit.

Desired Skills:

• Experience working with embedded Linux, Automotive Android
• Knowledge of vehicle data interfaces (CAN, OBD-II, sensors).
  • Exposure to LLMOps & MLOps pipelines and cloud platforms (AWS/GCP/Azure).