Lead/Senior Software Engineer, Health Algorithms and Deep Learning
at Magic Leap, Inc.
Plantation, FL OR Remote
As Lead or Senior Software Engineer, Health Algorithms and Deep Learning, you are responsible for combining and fusing spatial and visual computing paradigms to define novel biomedical algorithms for health and fitness applications. You will work on the development of the biomarker algorithms of our spatial health computing framework, contributing directly to exploration and development. You will work closely with program management, the health platform, systems and applications teams, the data collection team, and the regulatory team to ensure the development of efficient and highly robust clinically validated algorithms.
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.
Develop optimization methods, deep learning architectures, and tools to ease the use of feed forward and recurrent models.
Design computationally efficient 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.
Write elegant, maintainable, reusable code, leveraging test driven principles to develop high quality algorithms and services.
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.
7+ years of industry experience as a software algorithm developer.
5+ years coding & debugging of C++ and Python.
3+ years of experience working in healthcare or medical device development.
Proven track record of bringing deep learning algorithms from applied research and feasibility to production-level implementation.
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 or medical applications required .
Knowledge of deep learning frameworks, especially TensorFlow, required.
Knowledge of computer vision algorithms is a very strong plus.
Knowledge of biomechanics or applied physiology 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.
Ph.D. in Computer Science, Biomedical Engineering, or related with concentration on machine learning required.