Sandbox AQ - Palo Alto, CA

posted 5 days ago

Full-time - Entry Level
Palo Alto, CA
Publishing Industries

About the position

As a biomedical engineering (BME) post-doc on our medical quantum sensing team, you will help develop device prototypes, configure them for data capture to validate design choices, and analyze sensor data to drive design decisions in our product development towards FDA market clearance. In this role, you will work cross-functionally with our hardware, software platform, and machine learning teams to ensure our device performs with actionable diagnostic insights in our users' clinical workflow. A successful BME postdoc will serve as the bridge connecting hardware features under test to the pre-ML signal processing pipelines whose performance depends on them. This individual owns the hardware validation process that will ensure our product is successful in a pivotal clinical trial, and is transformative for the future of cardiac care in the emergency department.

Responsibilities

  • Configure cardiac sensor hardware to stream useful data in various stages of prototyping during development.
  • Analyze signal processing pipeline outputs to identify hardware + platform issues, and recommend iterations to the developing product.
  • Work with sensor physics, mechanical engineering, and machine learning teams to develop validation experiments that derisk device concepts along the development path.
  • Develop verification and validation test bench systems and automated frameworks for acceptance testing of devices.
  • Assemble functional prototypes and pre-pivotal study devices, and deploy devices to clinical study sites.
  • Become an expert operator of our cardiac devices, able to train clinicians and recommend device improvements.

Requirements

  • Recent doctoral degree in biomedical engineering or related fields.
  • Familiarity with verification and validation concepts.
  • Proficient in defining and articulating user & product requirements.
  • Proficient in signal processing methods for time-series data.
  • Proficient in data analysis and pipeline development in Python (including numpy, scipy, etc.)
  • Proficient in hardware configuration and debugging.
  • Track record of creating and analyzing benchtop prototypes for early testing.
  • Familiarity with medtech device development and approach to FDA clearance, especially for class II devices.
  • Track record of working successfully with cross-functional collaborators (e.g., Hardware & Software Engineering, Machine Learning... etc.)
  • Ability to present complex technical information in a clear and concise manner to a variety of audiences
  • Possess a growth mindset. Always seeking new learning opportunities, both professionally & personally.

Nice-to-haves

  • Proficiency with mechanical engineering and design, including CAD software (e.g. Solidworks, Fusion360)
  • Proficient in electrical engineering sufficiently to create and debug PCBs
  • Experience with embedded and/or real-time hardware
  • Experience with cloud-based data ecosystems
  • Proficient in classical signal processing methods
  • Experience training machine learning models
  • Experience working directly with clinicians, physicians, and hospitals.
  • Experience in cardiology (interventional cardiology, electrophysiology) and/or emergency medicine
  • Experience with development of novel diagnostic devices
  • Experience excelling in a fast-paced, startup environment
  • Awareness and understanding of the latest market & policy trends in healthcare.

Benefits

  • Competitive salaries
  • Stock options depending on employment type
  • Generous learning opportunities
  • Medical/dental/vision insurance
  • Family planning/fertility benefits
  • PTO (summer and winter breaks)
  • Financial wellness resources
  • 401(k) plans
  • Annual discretionary bonuses and equity
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