Embedded AI Developer

2 weeks ago

Austin, Texas, United States Ambiq Full time
About Ambiq

Ambiq is a leading developer of ultra-low power semiconductor solutions that enable intelligent devices everywhere. Our mission is to drive a more energy-efficient, sustainable, and data-driven world by developing innovative technologies that reduce power consumption while delivering maximum feature sets in compact industrial designs.

Job Overview

We are 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 sophisticated machine learning and deep learning models on highly constrained environments. Your expertise will be crucial in enabling state-of-the-art ML and DL model development across our hardware portfolio.

Key Responsibilities
  • Identify, refine, and/or develop sophisticated ML and DL models for deployment on highly constrained environments.
  • Train models using state-of-the-art 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 your achievements via conferences, meetups, workshops, and publications.
Requirements
  • Experience with state-of-the-art pruning, distillation, and 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) experience is a plus.
  • Dataset creation and curation skills are essential.
Bonus Qualifications
  • Past involvement or experience in TinyML.
  • 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 heterogeneous AI compute (e.g. CPU+NPU+DSP).
Education and Experience

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

The salary range for this position is $95,000-$165,000.

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