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Machine Learning Scientist: Supply Chain
Bring the force of your knowledge to global health and crucial supply chains to solve desperate problems in some of the world’s most challenging environments.

The Macro-Eyes Machine Learning Scientist: Supply Chain will build cutting-edge machine learning that powers products for crucial supply chains: save lives + enable organizations to do more with less. 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.

Responsibilities in this role include: Strong drive to use ML for social good, and solid background in machine learning. Statistics and experience working with messy data are 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.

  • 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, 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.
  • Strong self-motivation and self-management.
  • Ability to work in a fully remote setting.
  • Effective verbal and written communication skills.

ADDITIONAL JOB REQUIREMENTS

What we’ll ask of you:

  • Take a task and run with it. There’s not a lot of hierarchy, and everybody organically occupies the space they’re given to get something done.
  • Speak up. We all learn every day. We constantly figure out things we’ve never done before. Ask for help, say when you need something.
  • Be forthcoming and accountable. About time, scope, questions, needs, options, deliverables.
  • Be nice to work with. Nothing extraordinary was ever achieved alone.

What you need to bring:

  • A data-first mindset with a proven track record of delivering successful products.
  • Comfortable working with a small team in a fast-paced, collaborative but unstructured environment.
  • Experience working on dynamic cross-functional teams.
  • Strong written and oral communication skills.
  • Energy, boundless curiosity, open-mindedness.
  • Care to do something right for the sake of doing it right.
  • Willingness to learn and grow.
  • Respect for audiences and users. Willingness to step into someone else’s shoes (and the imagination to do so).

We’re excited if you also have these capabilities:

  • Experience working with teams using Agile development processes.

Why you want to work with us:

  • We develop technology and products that save lives and help organizations do more with fewer resources — and we break new ground in AI by creating systems that can learn in some of the most challenging environments on earth: real-world impact and state-of-the-art science.
  • We are rapidly growing — globally — and engaged in many of the most important issues of our time.
  • Being part of Macro-Eyes is rich in opportunity.
  • You get the chance to shape the world, bend it towards progress!
  • You get to work with an amazing group of people.
  • You can work from almost anywhere, although less than 6 hours from EST tends to be optimal.
  • 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.

ABOUT MACRO-EYES

MACRO-EYES is an AI company. Our technology makes crucial systems predictive. Predictive systems are resilient.

Radical thinking is at our core.

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, 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, private investors and USAID and has partnered with Stanford, 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.

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 predict 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.

The Macro-Eyes team is spread across Zambia, Kenya, Germany, Switzerland, South Africa and works from all corners and peninsulas of the United States. We believe in recruiting the best talent in the world, regardless of location — particularly now! This role will be remote with the freedom to choose how and when to work. Our remote team was executing at the highest level before COVID-19, and we expect to continue to be a fully remote, high-performing team. 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.

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 with hands-on experience building predictive models.

If you do have a Github profile, kindly include your work reference or link in your resume.

Disclaimer: Due to large volumes of applicants, only shortlisted candidates will be contacted.