Machine Learning Engineer
at Gousto in London
Technology, Data Science and AI are at the heart of Gousto. The code we write powers every aspect of our business from the recommendation engine powering our e-commerce experience right down to the genetic algorithms used to efficiently route boxes in our warehouse.
We use the latest technologies to create simple and elegant solutions to complex problems. We’re ‘all in’ on AWS using many of its services. Our platform and continuous delivery pipeline is fully automated using Cloudformation & Ansible, we release code to production multiple times a day and we’re in the process of moving our microservices architecture to containers. We build our services in Python, PHP and Node.js with a significant proportion now delivered via AWS Lambda.
Who you are
A passionate and talented (Machine Learning) Engineer, passionate about building and improving a world class Machine Learning (ML) platform to ensure all our ML algorithms touching most parts of the business are getting smoothly deployed in production, performing as expected and keep moving our KPIs.
An ideal candidate has a proven track record in deploying code in production (ideally algorithms) using CI/CD pipeline and has a blend of excellent coding skills and passion for AI, especially with understanding of all the challenges that comes with ever-changing data.
Most of all you are excited about what we do at Gousto and really enjoy working with the team.
What you’ll do
- Own and improve our ML platform – we invested heavily in AI to build the leading customer proposition in the market. We are committed to enable our Data Scientists to seamlessly build, deploy, and operate ML algorithms at scale. We’ve massively improved our CI/CD pipeline for our ML algorithms since we built the first algorithm, but you will help us to build the ML platform to standardise the way how we develop, deploy and track our ML algorithms in production.
- Help to drive our long-term AI strategy – although we already have numerous ML algorithms running in production we are still at the beginning of our (AI) journey and will keep investing significantly in AI capabilities going forwards. Helping to build a truly great ML platform and AI strategy will be a hugely important part of what you do.
- Be obsessed over quality – as a ML enthusiast you must have already heard a quote “garbage in, garbage out”. To ensure high-quality of our ML algorithms you will write enterprise quality, clean and readable code, and work closely with Data Engineers to ensure every data-point in the pipeline is valid. On top of that you will work closely with Data Scientists to design our data products.
- Must haves
- Working understanding of ML algorithms – you will be working with ML algorithms on a daily basis, thus understanding them in a nutshell is a must for this position.
- Strong programming and software design skills (Python) – you should be confident using pure Python, to write anything from a simple script to an application using OOP.
- A proven track record of using CI/CD pipelines – automating development and deployment pipelines for ML algorithms will be your main job.
- Keen to learn new technologies – ML(Ops) is a very young branch of Tech and it is evolving super fast, so following and learning new technologies is crucial to keep up with it.
- Experience with cloud technologies – all our tech lives in AWS.
- Being pragmatic – things can change very quickly in our team, but we stay focused on our goals – you must be comfortable working in such environment.
- Good communication skills – you will be working closely with Data Scientists and Data Engineers discussing very complex topics, thus explaining things in clear way is very important.
Nice to haves
- Experience with containers – we run our ML algorithms as containers.
- Experience with scientific libraries for Python – numpy, pandas, scipy, etc..
- Experience with Airflow – it’s our main task orchestration tool.
- Experience with code profiling and optimisation – ideally Cython.
- Experience with any ML platforms, e.g. mlflow, pipeline.ai – there is a huge demand for a platform in ML community and we want to be part of it.
- Experience with distributed systems.
At Gousto we feel it’s massively important to hire adults and give them the freedom to get things done. We don’t judge your performance by hours at your desk, but by the impact you have. While our office hours are 9am to 6pm, as long as people attend the morning stand-up for their squads the hours are flexible around this. Our only requirement is that you follow our ownership principles and Put Gousto First. Flexible working is widely practiced, but we are not a remote company and the majority of the time should be based in our Shepherd’s Bush office.
- “Tech 10%” – use every other Friday to sharpen your own skills and work on your own projects
- Holidays – 25 days of holiday (plus bank holidays) increasing by a day each year up to 30 days
- Option to buy additional days of annual leave up to a total of 30 days
- Discounted Gousto boxes – 40% staff discount on Gousto boxes and 25% for your family and friends plus your first box free
- Dr Gousto Healthcare via Babylon Health
- Access to Gousto Academy training courses
- Gym Membership
- Cycle to work scheme
- Quarterly team socials and mixed team events
- Coffee/ Tea, fruit and ice cream provided every single day to keep you fresh
- Friday socials – Wine, beer and soft-drinks
We are hugely committed to equality of opportunity in all areas of Gousto. We employ over 20 nationalities and think it’s deeply important to have all genders represented in all functions and levels. All individuals will be treated in a fair and equal manner and in accordance with the law regardless of age, disability, gender, pregnancy and maternity, marital status, race, religion or sexual orientation. We know, based on research, that some people are less likely to apply for this role. Please consider the above bullet points as guidance (our perfect candidate may not meet 100% of them) and if you feel you would be suitable for this role then please get in touch.
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