Embedded ML Engineer: Real-Time On-Device AI
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Summary
Embedded ML engineer deploying machine-learning models onto wearable, audio, and other intelligent devices. Day to day: moving research models to production on resource-constrained hardware, training/fine-tuning with PyTorch or TensorFlow, and writing high-performance C/C++ for on-device inference optimized for latency, memory, and power.
Intelliswift - An LTTS Company is seeking an Embedded Machine Learning Engineer to deploy ML models on wearable, audio, and intelligent devices. The role emphasizes transitioning research models to production on resource-constrained hardware with a focus on latency, memory, and power efficiency. The candidate will train and fine-tune models using PyTorch or TensorFlow and develop high-performance C/C++ software for on-device inference, working closely with researchers and engineers in a J-18808…