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Tier-1 brand, metro Bangalore, mid-level ML role with broad AI skillset increases candidate competition.
Requires specialized ML inference, quantization, and edge device expertise, limiting cross-industry transferability.
Explicit 3+ years minimum plus specialized ML inference, quantization, and C++/Python requirements enforce strict filtering.
Develop AI tools for tuning generative AI and multi-modal models targeting XR and wearables products.
Research and develop techniques for AI inference optimization including graph optimization, quantization, pruning, and compression to balance performance, accuracy, latency, and power.
Work on deployment and scaling of AI models (including GenAI, LLMs, and MVNs) for energy-efficient wearable devices.
Bachelor's degree (Engineering, IS, CS, or related) with 3+ years, OR Master's degree with 2+ years, OR PhD with 1+ year relevant Systems Engineering experience.
Strong hands-on programming skills in Python and C++ (level >7/10).
Experience with ML/AI tools development involving Deep Learning frameworks like PyTorch (1.x, 2.x), TensorFlow, Executorch, or ONNX.
Strong understanding of model architectures in CV, NLP, LLMs, LVMs, multi-modal networks and inference graph optimization, quantization, and compression techniques.
Experienced in performance tuning and troubleshooting of neural network accuracy and inference speed issues.
Comfortable working on advanced optimization methods and researching industry trends for AI model acceleration on edge devices.
Familiar with AI runtimes and frameworks, and has a systems engineering mindset towards integrating and scaling AI software solutions.