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:
- Explore and implement ML models using the world’s largest dataset of over 600M construction activities.
- Coach and mentor other ML engineers and shape how we do ML (and more!) at nPlan.
- Own the entire model lifecycle and pipeline, from training through continuous deployment to the live deployment.
- Build and deploy models that scale to our continuously growing product’s needs.
- Collaborate with our research team to learn and share knowledge (such as at our ML paper club!) and validate new ideas with ML experiments.
- Experience leading the use of ML in production systems at scale.
- A postgraduate degree in a relevant field, or equivalent experience with machine learning and statistics.
- Knowledge of at least one deep learning framework (such as Tensorflow or PyTorch).
- Strong knowledge of Python or C++ and algorithmic programming.
- Experience with data exploration, analysis, and visualisation.
- Familiar working with version control and collaboration tools (ideally Git & JIRA)
- A track record of mentoring and helping other engineers grow to meet their potential.
- Please mention the word ‘crane’ in your application.
- (bonus) contributions to relevant open source projects
- (bonus) knowledge of how to build for cloud-native systems
- (bonus) experience optimising ML code using high-performance frameworks
What working at nPlan will be like:
- We are still a relatively small team so there is plenty of opportunity for a high degree of ownership over different areas of the product, and you will be directly exposed to all areas of the business.
- Your voice will always be heard. What you do or say counts, not who you are or where you're from.
- We have three core values that underlie everything we do: Learn from Everything, Be Radically Truthful, and Aim High, Run Fast. These enable us to create a collaborative, inclusive environment where we can move effectively and efficiently to implement the best solutions.
- We are a cross-disciplinary team, and come from all backgrounds and countries. We offer Visa sponsorship and contribute to relocation costs (role dependant).
- Fantastic benefits package for Health & Wellbeing, Learning & Development, family leave, weekly team meals and more.
- We are committed to addressing the diversity problem in the tech industry, and that starts with making sure we have a diverse team where everyone feels at home and can contribute as an equal.
- Having time to yourself and a private life is important. We offer a very flexible work environment and a generous holiday policy.
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.