Data Scientist

Artificial Intelligence
U.S. (any location)

Scope and Responsibilities:

At Ambiq®, the Endpoint AI team enables state-of-the-art ML and DL model development across our hardware portfolio, using sophisticated model compression techniques to deploy previously impractical AI tasks to battery-powered environments. Our team of data scientists research model architectures best suited to our customer’s needs, select those models most amenable to deployment on our platform, and train them carefully tuning for memory, compute, and energy constraint tradeoffs. Finally, we publish our findings to our ModelZoo/Garden and socialize them via conferences, workshops, and publications.

Beyond a healthy obsession with computational efficiency, the successful candidate will be comfortable with operating in a ‘version zero’ environment, marshaling internal, open source, and third-party resources to solve our customer’s problems quickly and elegantly.

Specific 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 ModelZoo/Garden, including Jupyter Notebooks, documentation, and other assets needed by our customers to bootstrap their internal AI features.
  • Socialize their achievements via conferences, meetups, workshops, and publications.

Required Skills and Abilities:

  • 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, and/or time series tasks, including domain-specific feature extraction related to those tasks.
  • Tensorflow (TFLite, TFLite for Microcontrollers, MicroTVM, and/or PyTorch/Glow are a plus).
  • Dataset creation and curation.

Bonus Qualifications:

  • Past #TinyML involvement or experience
  • Experience developing and optimizing for TFLite for Microcontrollers
  • Experience with compression of attention-based architectures
  • Experience with Glow or other model-to-binary compilers
  • Experience with ONNX, ONNX runtime, and/or MLIR
  • Experience with optimizing for heterogenous 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.
  • Experience developing ML and DL models in Tensorflow and/or PyTorch.
  • Experience with model compression techniques.
  • Experience creating and maintaining datasets in the audio or time-series domains is highly desirable.

Key Personal ad Professional Attributes:

Ambiq is a company that values continued technology innovation, a fanatical attention to customer needs, collaborative decision making, and, above all, enthusiasm for energy efficiency. The incoming candidate should embrace these same values. The successful candidate must be self-motivated, extremely creative, and should be comfortable learning exciting new technologies. This is an opportunity for growth and an opportunity to work on complex, interesting, and challenging projects.

Company Overview:

Ambiq is bringing intelligence to billions of endpoints. Using the revolutionary Sub-threshold Power Optimized Technology (SPOT) Platform, Ambiq’s record-breaking ultra-low power SoCs free device makers to put intelligence everywhere. Ambiq’s SoCs have enabled more than 100 million battery powered devices in markets ranging from wearables to hearables to smart credit cards to smart home devices to smart industrial devices. Ambiq develops and sells SoCs and software solutions with innovative and fast-moving teams in the US (Austin and San Jose), Taiwan (Hsinchu), China (Shenzhen and Shanghai), Japan (Tokyo), and Singapore.

We are just getting started with this first 100 million devices. Come join us on our quest for 100 billion devices. The endpoint intelligence revolution starts here.

Please submit resumes to [email protected] or complete the form below.

Submit a resume