Salary: Competitive - Start Date: ASAP
We need your help. One of the major blockers to our growth plans is the way we currently manage and maintain all of our data. It’s worked really well for us up until this point, but it simply won’t scale with us at the rate we want to go.
We recently spun out a separate Machine Learning team and we’re looking for someone (you, we hope?) to help us put into production all the various models we’re building to improve the efficiency of our data collection and management systems. In this role, you would contribute to the direction of our ML team & be a driving force behind our growth and ongoing success.
If this sounds exciting, please read on...
Through our platform, we’re the market leading provider of data on the fastest growing companies in the UK (think Monzo and Babylon!). Over the last few years, we’ve introduced machine learning into our tech; putting some exciting models in place which have helped to enrich our existing data and speed up or eradicate various routine tasks. Now we are looking to accelerate this work and we need a versatile, enthusiastic Machine Learning Ops Engineer to help us productionise everything more efficiently.
Our Machine Learning team is looking to expand into three key areas:  enabling us to significantly expand the depth and breadth of our data,  empowering our Data Team to handle this expansion, and  building tools that help our customers make better data-driven decisions.
Your responsibilities will include:
- Data collection – our data is collected from a variety of sources (from press releases to company filings to job ads) by two methods: automated tools & human curation. You’ll help us build systems to support both, which could be scraping tools or internal interfaces for decision makers.
- Data pipelines – machine learning models are only as good as the technology that allows them to perform. You’ll get to build and improve upon the pipelines that help us to understand and measure our data processes.
- Monitoring – diagnosing problems quickly by building systems that detect changes in the source data or problems with our underlying assumptions
- Deployment – productionising ML models that are fit to solve a business problem – this could require fast prediction or an interpretable model, you’ll help us choose the right models and build systems for their implementation & monitoring.
Examples of the kind of problems would you be working on:
- We currently use various systems to extract & organise structured data from our mostly text-based sources (press releases, company filings, etc.) – namely natural language processing, entity recognition, classification and embedding systems. There are exciting opportunities in this area both from finding new sources and exploiting new techniques.
- Our data-set is made up of a complex network of rich entities (companies, people, transactions, etc.). We use a variety of techniques, such as semi-supervised learning or graph clustering to connect these entities, but there’s always new, interesting ways to find these connections.
- A lot of our data is event based and requires various levels of human input. We build systems that enable that human input to be focused and effective, such as decision support systems or auto-suggestion. We think there are lots more systems we can create to help support our Data team.
These problems, and many more, require thinking creatively about the ways machine learning can be applied and we’d love for you to help us by contributing ideas & putting them into practice
There is no one size fits all for this role, but we are ideally looking for someone who has either a postgraduate degree in ML (or equivalent), or has at least 2 years experience working with ML.
Ideally, you will be:
- Adaptable - you are a generalist who is willing to take a flexible approach to a broad range of responsibilities.
- Independent and proactive - you are happy to take on your own projects & the opportunity to lead their exploration, development and delivery excites you.
- A team player - you work well with others, can argue your case & make suitable compromises and you want to grow within the team & contribute to defining it
Great to have (but not essential):
- Experience with general tools for machine learning - e.g. scitkit-learn, scipy, numpy, pandas, jupyter, tensorflow, pytorch, networkx….
- Experience with scraping and knowledge extraction tools
- Experience with general software development processes – e.g. git, docker, the pull request process, linting, etc.
We're offering a competitive starting salary, depending on experience.
On top of this, we invest a lot in keeping our people happy and healthy! So as well as that, you'll also get:
- Training: Structured training & ongoing personal development
- Wellbeing: Free coaching, counselling and virtual yoga/mindfulness sessions
- Socials: Drinks every Friday, office parties, company away days and regular team events
- Options: Substantial options scheme, so you can share in the growth you help create
- Talks: Interesting speakers in the office and on Zoom
- Snacks: Unlimited supply of healthy snacks and drinks
- Books: You can order any relevant books you like or come along to our book club evening
- Travel loans: Rail season ticket loan and cycle to work scheme
- Hybrid working: Flexible office & remote working – see below for more details
We are the market-leader for tracking the most exciting companies in the UK. Through a combination of people power and machine learning, our data platform helps over 20 different industries invest in, understand, and partner with start-ups and scale-ups all over the country.
Other than the product, our real key to our success is our wonderful culture. Based in the heart of vibrant Brixton, we’re a supportive, close-knit group with a range of interests and quirks - from bakers, to artists, to beer-brewers to gamers. To drive our company forward, we take responsibility for our work & embrace our mistakes, continually challenge ourselves & each other to do better, and be proactive & energetic in everything we do!
Like most companies, we’ve been umm-ing and ahh-ing about this for months, trying to work out what the perfect balance between in-office and remote working should look like for us. And we’ll be totally upfront with you – it’s really hard! We don’t yet know what exactly our policy on this should look like long term. But we’re keen to share our current thinking and some of the things that (we think) we know for sure. We’d also love to chat to you more about this in the course of the interview process so please do ask us questions!
And what are we doing at the moment?
- We’re currently running a trial, during which we’re asking everyone to spend at least 60% of each month in an office (London or Nottingham)
- We’ll be reviewing how this is going in February and again at the end of the trial – we'll take into account how everyone in the company is finding it, how managers think it's going, as well as considering it from the "company perspective"
Ticking all the boxes?
To apply please submit:
- Your updated CV
- Answers to a couple of simple screening questions below