Machine Learning Engineer - London, United Kingdom - eFinancialCareers

eFinancialCareers

Verified Company

London, United Kingdom

1 week ago

Posted by:

Tom O´Connor

beBee Recruiter

Description

Join us as a Machine Learning Engineer

In this role, you'll be driving and embedding the deployment, automation, maintenance and monitoring of machine learning models and algorithms
Daytoday, 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 solutionsdriven 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, includingpipeline optimisation.

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 multidisciplinary 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 toresolution.

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, TeamCityand CodeDeploy.

You'll also need:

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
To be a Docker and Kubernetes developer or have administrator experience and an interest in becoming Kubernetes certified