Groundbreaking AI for true social good.
Build and implement machine learning to shape the future of supply chain. Our work is supported by the Bill & Melinda Gates Foundation, USAID, and private investors.
You will create transformative solutions the world has never seen. We are working on unsolved problems at the nexus of state of the art of machine learning and crucial supply chains: the first predictive supply chain for health; a new, deployed system for understanding demand for lifesaving care; computer vision and deep learning to automate ground-truth data collection when compute has to run entirely on device; deep learning on satellite imagery to derive features that help us understand the ‘context for care’; location inference accurate to within 25M when GPS is unreliable; human-in-the-loop machine learning with experts on the frontlines to learn what we don’t know and generate real-time insight. Go beyond theory: what you build will become products, deployed across the developing world - and for some of the most sophisticated consumers of technology in the world - to shift crucial supply chains from reactive to proactive, capable of anticipating risk and opportunity for governments and corporations. Your work will save lives.
If this challenge is intriguing, please apply to be a Machine Learning Scientist at Macro-Eyes here.
Macro-Eyes is working towards a future state in which the delivery of care is predictive everywhere, where supply chains that deliver essential goods anticipate need and demand down to the individual and ensure the right resource is used at the right time, personalizing care, increasing access, and making scarce resources serve more people in need. You will build the future.
Ad-Optimization it is not. We believe that the state of the art in machine learning will come from confronting fundamental challenges in the most difficult environments in the world. Engage where the problems are hardest and AI too will benefit: smarter, faster, cheaper.
MACRO-EYES technology makes crucial systems predictive. Predictive systems are resilient, enabling our customers to save lives and extend the impact of scarce resources. We have a mandate to deliver social impact, a global presence and an international machine learning team led by MIT faculty. The Macro-Eyes team has built and shipped cutting-edge machine learning systems that run at large US health systems and on-device in the most challenging environments in the world. Macro-Eyes is supported by the Bill & Melinda Gates Foundation, the Draper Richards Kaplan Foundation, and USAID and has partnered with Stanford, the US Air Force Research Laboratory, UNICEF, the Government of Tanzania, the Government of Mozambique, the Government of Sierra Leone, and Direct Relief. Accenture spotlighted Macro-Eyes product Sibyl as critical digital health technology of the future.
Strong drive to use ML for social good, and solid background in machine learning. Statistics and experience working with messy data a plus. Python fluency needed. Demonstrated ability to make meaningful contributions to projects with a research flavor is valuable. The successful candidate will be excited by the fact that the work we will do together is largely without precedent.
Warning: the work will not be like doing data science at Big Tech: the data will not be pristine and what’s required for success is much harder than throwing a series of models at the problem. We expect you to think in terms of hypotheses and experimental design like a scientist and have the drive and ingenuity of a hacker.
hands on experience building predictive models
happy to dive into data
building models based on empirical results, and understanding of the strengths and limitations of this approach
experience working with diverse data types including images and structured data and natural language
Experience programming in Python, and one additional language (R, C, C++, Java)
Aware of current best practices in machine learning
Knowledge of statistics, including hypothesis testing with parametric and non-parametric tests and basic probability
Experience building different deep neural network models or knowledge of graph theory is preferred.
‘Small data’ experience: demonstrated ability to develop and implement creative approaches for making machine learning work with limited conventional data.
This role will be remote with the freedom to choose how and when to work. Macro-Eyes was fully remote before COVID-19 and we expect to continue to be a fully remote team. US-based candidates are preferred. You will have access to your choice of hardware and a travel budget to interact with the distributed team in person. Macro-Eyes has a rigorously horizontal culture that values diversity of every kind.
Competitive compensation and generous benefits.
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.