Software Engineer. Implement cutting-edge AI to save lives and preserve rare resources.

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Groundbreaking AI for true Social Good.

Build and implement machine learning to enable an ambitious vision for the future of healthcare – save lives now and help shape the future of health at global scale. Design and develop strategic software to improve access to care in US and global health. Build efficiency and accuracy into core software infrastructure to enable scalability and transparency.  Streamline software to improve efficiency, implementation, and adoption.

Learn and grow with one of the best machine learning teams in the world, led by MIT faculty and advised by renowned technologists, scientists and experts in machine learning (MIT, UCL, Imperial) and global healthcare leaders.

You will create transformative solutions the world has never seen. What you build will enable access to essential health care and health goods around the world. Your work will contribute to the most advanced technologies being deployed in healthcare. You will collaborate with global leaders in health, supply chain, and global development. Your engineering will solve the last-mile problem in AI: transforming predictions and insight into systems that directly solve problems and save lives. We bring machine learning technology to bear on the most difficult challenges in the world – delivering to-date unachievable levels of health access and health equity.

macro-eyes is an AI company rebuilding the foundations of health to make the delivery of care predictive everywhere. We have a mandate to deliver social impact, global presence and international machine learning team led by MIT faculty. macro-eyes has built and shipped cutting-edge machine learning systems that run in the wild at leading academic medical centers in NYC and California and at one of the largest heart hospitals in the US. macro-eyes is supported by the Bill & Melinda Gates Foundation, the Draper Richards Kaplan Foundation, and USAID and has partnered with Microsoft, Stanford, the Government of Tanzania, and the world's largest academic clinical research organization. Accenture spotlighted macro-eyes product Sibyl as digital health technology of the future.

Expected qualifications

Strong drive to use technology for social good, and solid background in software engineering. The ideal candidate will be self-driven, creative and work well with the inherent ambiguity of developing truly new technology. Demonstrated ability to make meaningful contributions to projects when there wasn’t an obvious model of what to do next. The successful candidate will be excited by the fact that the work we will do together is largely without precedent.

macro-eyes has employees in the United States in Washington, DC, Seattle, and Boston and in Bielefeld, Germany. We believe in recruiting the best talent in the world, regardless of location. The role will be remote with the freedom to choose how and when to work. You will have access to your choice of hardware and will have a travel budget to interact with the distributed team in person. macro-eyes has a rigorously horizontal culture that values diversity of every kind.

If this challenge is intriguing, please get in touch with benjamin@macro-eyes.com

Experience/Abilities (in more detail):

  • Hands on back-end engineering experience

  • Experience working in Python and Django

  • Development of data visualization for internal and customer facing use

  • Experience developing reporting tools for evaluation of technologies a plus

  • English proficiency

  • German and/or French language skills a plus

  • Experience with unit testing for new and existing software

  • AWS and/or Azure experience a plus

  • Knowledge of statistics, including hypothesis testing with parametric and non-parametric tests, basic probability

macro-eyes is dedicated to building an inclusive workforce where diversity is valued.

macro-eyes is an equal opportunity employer. Every qualified applicant will be considered for employment.

macro-eyes does not discriminate based on race, color, religion, gender, gender identity or orientation, genetic information, age, national origin, marital status, disability status, political ideology, military or protected veteran status, or any other characteristic protected by applicable federal, state, or local law.