Machine Learning Engineer (UK)
Salary - up to £60,000 + great benefits
QA & Testing is often seen as an unexciting though necessary aspect of the software development process.
We’re here to change that.
We’re working hard to develop exciting new technologies, harnessing the power of machine learning and combining this with extensive domain expertise to enable testing to be performed fully autonomously. Something akin to self-driving cars of the testing world!
We know this is no easy feat, but nothing worth doing ever is. If you’re excited and inspired by the prospect of working with a team of highly educated, expert engineers from around the world to build ground-breaking, and dare we say game-changing, applications to make testing easier, more efficient and autonomous, then we’d like to talk with you.
You’ll have the freedom to make decisions quickly and execute them, to work collaboratively with colleagues in other countries, (advanced written and spoken English is a must), and you’ll be able to apply your experience and education (degree or equivalent) to help us develop a robust and scalable enterprise product to allow organisations to test their software faster and more effectively than ever possible before.
Here’s a glimpse of some of the projects you’ll work on and lead as a Machine Learning Engineer
- Building intelligent anomaly detection techniques
- Automatic summarisation of large-scale test results
- Automatic model inference
- Improve our existing models and classifiers and help us research/develop new ones
- Build ML algorithms and integrate, or support integration with our product
Essential skills you’ll need:
- Strong practical and theoretical experience with machine learning.
- Some understanding of Java in order to integrate ML algorithms into our codebase
- Strong abilities to wrangle and clean data
- High proficiency with the Linux command line
Additional experience that is welcome:
- Strong programming skills in at least one major programming language (e.g., Python, Java, C++)
- Conducted self-directed academic research and be comfortable setting a research agenda.
- Be a champion of quality - software design patterns and passion for writing clean code
- Have worked as part of a team to deliver high-quality software to a production environment
- Be comfortable reporting results to stakeholders and informing strategic decision-making
Bonus Points for:
- A postgraduate degree (preferably PhD) in a relevant machine learning topic.
- Polyglot: can program effectively in a wide range of programming languages and frameworks.
- Experience with distributed systems (concurrency, consistency, partition tolerance)
We know that as a Machine Learning Engineer you’ll have a mix of different skills, technologies and experiences, so we’ve tried to keep our ‘wants’ to a minimum, and thought sharing details of our tech stack would be more interesting to you.
Our Tech Stack:
- Java services (distributed architecture)
- PostgreSQL for relational database
- Vue / VueX for frontend
- Consul for discovery
- AWS (ECS, S3, CloudFront, ALB)
- Prometheus for metric monitoring
- ELK for logging
- Terraform for infrastructure management
- Github for source control
- CircleCI for CI / CD
- Your favourite technology that can help solve challenges
What else is in it for you?
- The opportunity to bring your own ideas to reality (we love new solutions and ideas!)
- Team retreats every 6 months... somewhere nice because you’ve earned it!
- Full Jetbrains pack license (IntelliJ et al)
- Private health insurance
- Take your birthday as holiday every year!
- Sabbatical opportunities
- Flexible and remote work options
- A new laptop and/or use your own equipment
We have a simple two-step technical assessment process as part of the overall interview:
We don’t expect you to write code in an unrealistic interview setting. To take away the stress of whiteboard tests, you get a small take-home challenge and you have a week to complete it (in a Gitlab repository that you can freely develop your code on) that will take no more than a few hours.
If we’re happy with your submission in step 1, we schedule a one-to-one Skype session to first provide you with detailed feedback on your submission, ask you a few more questions related to the code and solution you submitted and then it’s over to you to interview us. We make our decision after this stage, and you’ll hear from us with our final decision within 48 hours.
If you would like to hear more about this opportunity please feel free to contact Teo on 01908 886 030 or email@example.com