Machine Learning Engineer
|Published||November 12, 2022|
|Location||London, United Kingdom|
- In this role, you'll be driving and embedding the deployment, automation, maintenance and monitoring of machine learning models and algorithms
- Day-to-day, you'll make sure that models and algorithms work effectively in a production environment while promoting data literacy education with business stakeholders
- If you see opportunities where others see challenges, you'll find that this solutions-driven role will be your chance to solve new problems and enjoy excellent career development
What you'll do
Your daily responsibilities will include you collaborating with colleagues to design and develop advanced machine learning products which power our group for our customers. You'll also codify and automate complex machine learning model productions, including pipeline optimisation.
We'll expect you to transform advanced data science prototypes and apply machine learning algorithms and tools. You'll also plan, manage, and deliver larger or complex projects, involving a variety of colleagues and teams across our business.
You'll also be responsible for:
- Understanding the complex requirements and needs of business stakeholders, developing good relationships and how machine learning solutions can support our business strategy
- Working with colleagues to productionise machine learning models, including pipeline design and development and testing and deployment, so the original intent is carried over to production
- Creating frameworks to ensure robust monitoring of machine learning models within a production environment, making sure they deliver quality and performance
- Understanding and addressing any shortfalls, for instance, through retraining
- Leading direct reports and wider teams in an Agile way within multi-disciplinary data and analytics teams to achieve agreed project and Scrum outcomes
The skills you'll need
To be successful in this role, you'll need to have a good academic background in a STEM discipline, such as Mathematics, Physics, Engineering or Computer Science. You'll also have the ability to use data to solve business problems, from hypotheses through to resolution.
We'll look to you to have experience with machine learning on large datasets, as well as experience building, testing, supporting, and deploying advanced machine learning models into a production environment using modern CI/CD tools, including git, TeamCity and CodeDeploy.
You'll also need:
- Experience implementing DevOps and CI/CD for Python-based applications and libraries
- MLOps configuration skills on Cloud platforms, such as KubeFlow, TFX and Sagemaker
- Knowledge of Linux, Bash and Unix scripting, as well as an interest in automating Data Science experiences
- Working knowledge of PyTorch, Tensorflow, Scikit-learn, PySpark and their application to ML training and serving
- To be a Docker and Kubernetes developer or have administrator experience and an interest in becoming Kubernetes certified