Embedded AI Engineer
2 weeks ago
Ambiq is seeking a highly skilled Embedded AI Developer/Data Scientist to join our Endpoint AI team. As a key member of our team, you will be responsible for developing and deploying state-of-the-art ML and DL models across our hardware portfolio, using sophisticated model compression techniques to deploy previously impractical AI tasks to battery-powered environments.
Key Responsibilities- Identify, refine, and/or develop sophisticated ML and DL models for deployment on highly constrained environments.
- Train models using SOTA compression techniques to fit in specific memory, compute, and power envelopes, making trade-offs between compression and accuracy.
- Publish and maintain these models in a Model Zoo, including documentation, and other assets needed by our customers to bootstrap their internal AI features.
- Socialize their achievements via conferences, meetups, workshops, and publications.
- Experience with SOTA pruning, distillation, quantization approaches for CNNs and RNNs.
- Experience with one or more of the following AI task domains: audio classification, speech, vision, and/or time series tasks, including domain-specific feature extraction related to those tasks.
- Tensorflow (TFLite, TFLite for Microcontrollers, and/or PyTorch are a plus).
- Dataset creation and curation.
- Past "TinyML" involvement or experience.
- Experience developing and optimizing for TFLite for Microcontrollers.
- Experience with embedded C/C++ environments.
- Experience with compression of attention-based architectures.
- Experience with model-to-binary compilers (IREE, MicroTVM, etc).
- Experience with ONNX, TOSA, Jax, LLVM, and/or MLIR.
- Experience with optimizing for heterogenous AI compute (e.g. CPU+NPU+DSP).
A bachelor's degree in computer science or a related field is required with at least 2 years of relevant experience. A master's degree or PhD in related topics is highly desirable.
Salary Description$95,000-$165,000
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