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Principal Engineer, Algorithms and Deep Learning

If you have 10+ years of industry experience as a software algorithm developer, researcher and/or data scientist, Magic Leap, Inc. has a job opening for a principal engineer
Job post found at boards.greenhouse.ioApply for position

Description

Job Description

As Principal Engineer, Algorithms and Deep Learning R&D, Health, you are responsible for leading a team that fuses spatial and visual computing paradigms to define novel biomedical algorithms for health and fitness applications. You will own the development of the algorithms of the core user sensing service of our spatial health computing platform, ensuring the smooth functioning of the team while also contributing directly to exploration and development. You will work closely with program management, the health platform, systems and applications teams, the data collection team, the clinical and regulatory teams to ensure the development of efficient and highly robust clinically validated algorithms.

Responsibilities

  • Lead the algorithm development team to explore, research, prototype, design, develop and test methods and algorithms for health applications, including the detection and measurement of clinically and biologically relevant biomarkers, and assess their feasibility prior to productization.
  • Provide support and knowledge of algorithm development to the Director of Health R&D in the implementation of a comprehensive strategy for partners and end users.
  • Supervise the development of optimization methods, deep learning architectures, and tools to ease the use of feed forward and recurrent models.
  • Work with the clinical lead to research and understand the medical and clinical needs of partners and address these needs in the implementation of algorithms.
  • Define and coordinate the execution of data collection and analysis mechanisms and protocols.
  • Coordinate with the digital health platform team on the transfer of algorithms from applied-research feasibility phase to their implementation as production code.
  • Assist business segment leaders and systems engineering in capturing and understanding customer needs and translating them into system requirements.
  • Interface with hardware and software teams to ensure that needed features are placed in the product roadmap.
  • Ensure that the algorithm development team writes elegant, maintainable, reusable code, leveraging test driven principles to develop high quality algorithms and services.
  • Establish processes to create software, review code, and write documentation following medical device and HIPAA design controls.
  • Work closely with Software Security, User Experience, Hardware, Software, Business Development, Product, Clinical and Regulatory teams to implement the next generation clinically validated digital health biomarker suite for the device.

Qualifications

  • 10+ years of industry experience as a software algorithm developer, researcher and/or data scientist.
  • 8+ years coding & debugging of C++ and Python.
  • 5+ years of experience working in healthcare or medical device development.
  • Experience leading and managing algorithm development teams highly desirable.
  • Proven track record of bringing deep learning algorithms from applied research and feasibility to production-level implementation a strong plus.
  • Strong foundations in data structures, and software and computer architecture.
  • Experience in design of deep learning, other machine learning algorithms and other complex biomedical algorithms for health and wellness required .
  • Knowledge of deep learning frameworks, especially TensorFlow, required.
  • Knowledge of computer vision algorithms is a very strong plus.
  • Knowledge of biomechanics is highly desirable.
  • Experience in the development of algorithms for measurement and monitoring of health and medical applications is a strong plus.
  • Experience working in the medical device regulated (IEC 62304, FDA, MDD, HIPAA/GDPR, cybersecurity) industry desirable.
  • Proven ability and experience in using collected data to draw conclusions.
  • Strong experience with software practices such as source control, testing, code review. Knowledge and experience in usage of git is a plus.

Education

Ph.D. in Computer Science, Biomedical Engineering, or related with concentration on machine learning required.

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