Wefarm is the world’s largest knowledge sharing network for small-scale farmers.
Small-scale agriculture is the biggest industry on earth, with more than a billion farmers globally supplying 80% of the world's food and commodities. Yet these farmers remain digitally unconnected. No one has built such a sizeable network to solve this challenge … until Wefarm.
Using Wefarm, farmers can share and access vital information, products and services all from their mobile phones -- without needing any access to the internet. Since our launch in 2015 we have grown to have 1.4 million farmers on our network. They share more than 1 million questions and answers a month (that’s about 1 every 2.5 seconds!).
Wefarm has raised investment from some of the world’s leading investment firms including True Ventures in Silicon Valley and LocalGlobe in Europe. We are now looking to add to our world class team that’s based in London, Nairobi, Kampala and Dar-es-Salaam.
Join us and be a part of our mission to build a digital ecosystem for global agriculture with the farmer in the centre!
For the next stage in our growth, we are looking for an exceptional Lead Machine Learning Engineer (MLE) to help us to develop our next generation of Machine Learning (ML). At Wefarm, you’ll have a direct impact on millions of lives by building products that connect farmers to the information, services, and products they need to grow. You’ll have a unique opportunity to develop Natural Language Processing (NLP) tools in multiple regional, under-resourced languages – enabling fair access to ML for all.
You will be responsible for:
Developing a team – You’ll manage a team responsible for building ML libraries, tools, and algorithms, ensuring these work in-production and at scale. You’ll grow this team, hiring new staff members to add capabilities and perspectives. You’ll develop your team members’ skills through disseminating your experience and existing knowledge about ML, as well as strategically identifying opportunities for them to grow.
Driving research & development – We expect you to keep up-to-date with the latest developments in ML, communicating new opportunities to the whole team. You’ll evaluate and implement new-to-Wefarm technologies and services. You will take a lead role in planning and prioritising Wefarm’s ML capacities, including NLP in new languages, better candidate selection algorithms, and infrastructure.
Ensuring algorithmic fairness – At Wefarm, we understand that our farmers are the experts. Our product should be relevant, efficient, and intuitive: no matter your language, background, or culture. As part of this, you’ll be expected to lead a culture of algorithmic fairness in your team: understanding algorithmic bias, how it can manifest, and how to minimise it through good design.
Efficient & focused collaboration – You and your team will work closely with the Product and Engineering teams to design, build, and deploy new features and products. You’ll assist the Analytics and Insights team with additional technical support and training where necessary.
We are looking for someone who is passionate about solving complex global issues that affect billions of people, and want to help build a company at the forefront of accessible and fair ML.
In addition, you should be:
A passionate leader – You have the ability to lead a team to success, with experience hiring and mentoring. We’re looking for someone who can act a technical multiplier for their team. You’re always looking to develop your own leadership skills.
Commercially minded & focused – You understand Wefarm’s model relies on commercial success and growth towards financial self-sustainability. You focus on company priorities and ensuring your team gets to agreed outcomes as quickly and efficiently as possible.
An individual contributor – You have significant previous experience with ML, and have deployed ML in production systems and at scale. You’re fluent in at least one programming language. As part of the role you’ll be expected to become proficient in Clojure and other technologies currently used in Wefarm.
Due to the high number of applications we will only be able to respond to shortlisted candidates.