Graph analytics, Information Intelligence, Linear Algebra, Machine learning techniques, matplotlib, NumPy, Pandas, Python Programming, Scikit-learn, SciPy, seaborn, Statistics, TensorFlow
We are looking for a Senior Machine Learning Engineer to join our team in London or remotely.
Our purpose is to inspire the world to forecast correctly and empower it to tackle risk. In order to achieve that, we are continuously developing machine learning models and pipelines with the latest SOTA architecture or technology, such as Graph Neural Networks on a dataset with novel characteristics (our graphs consist of up to 450k nodes!). We have also been iterating on our own custom model performance metrics that suits what our clients need. We are also continuously improving our ML pipeline on serverless platform. We have a lot of exciting problems for you to solve and you would have the independence in choosing and developing the solutions.
We’re lucky to work on some of the largest infrastructure projects in the world, which gives us both an opportunity and a privilege to make a significant impact on the world around us, and what it will look like in the future, every day.
You’ll be joining a world-class and well-funded team, backed by top investors including GV (formerly known as Google Ventures) that all believe in the future we are creating. We’ve been on a tremendous growth trajectory for the last four years, and following our latest investment round we’ve got very ambitious growth plans for 2022 and beyond.
We know that taking your next career move is a big decision. If you'd like to ask us any questions before applying (role-related or company-related) please use this link to book in a short chat with our Talent Acquisition Manager, Jack
About the role:
You'll be solving some meaningful and interesting problems, with a strong technical team:
About you:
Nice-to-haves:
What working at nPlan will be like:
What your typical work week will be like:
As a Senior Machine Learning Engineer, you can expect to be working with other engineering and product experts, members of the Machine Learning chapter, and researchers. A typical week could involve a mix of focus time developing ML capabilities for our products, code-pairing with other members of your delivery squad, leading 1-1s with members of the ML chapter, and/or partnering with researchers to work out how to bring an idea to production. We operate in sprints with daily standups and use Slack, Jira, Github and Google Meet as collaboration tools.
At nPlan we are building the world's first system to understand construction project planning. We make heavy use of machine learning to forecast outcomes of construction projects before the first shovel hits the ground. Our vision is that all construction projects should be built on time and budget, through a better understanding of plan outcomes. We are bringing certainty of the outcome to the industry, plan first.