Machine Learning Engineer,AVP
2 weeks ago
Join us as a Machine Learning Engineer
- We're looking for someone to deploy, automate, maintain and monitor machine learning models and algorithms to make sure they work effectively in a production environment
- Day-to-day, you'll collaborate with colleagues to design and develop state-of-the-art machine learning products which power our group for our customers
- This is your opportunity to turn your interests into a diverse and rewarding career, as you solve new problems and create smarter solutions in a non-stop innovation environment
As a Machine Learning Engineer, you'll lead the planning and design of complex projects. Your daily responsibilities will see you codifying and automating machine learning model production, including pipeline optimisation, tuning and fault finding, as well as transforming data science prototypes and applying appropriate machine learning algorithms and tools.
We'll need you to deploy and maintain adopted end-to-end solutions, including building metrics to improve system performance and identifying and resolving differences in data distribution which affect model performance.
In addition, you'll be responsible for:
- Understanding the needs of our business stakeholders, and how machine learning solutions meet those needs to support the achievement of our business strategy
- Working with colleagues to produce machine learning models, including pipeline designs, development, testing and deployment to carry on the intent and knowledge into production
- Creating frameworks to make sure the monitoring of machine learning models within the production environment is robust
- Delivering models that adhere to expected quality and performance while understanding and addressing any shortfalls, for example through retraining
- Leading and working in an Agile way within multi-disciplinary data and the analytics teams to achieve agreed project and Scrum outcomes
To be successful in this role, you'll have an academic background in a STEM discipline, like Mathematics, Physics, Engineering or Computer Science. You'll need experience with machine learning on large datasets and an understanding of machine learning approaches and algorithms.
Alongside this, you'll have experience of building, testing, supporting and deploying machine learning models into a production environment, using modern CI/CD tools, like TeamCity and CodeDeploy. You'll also have good communication skills to engage with a wide range of stakeholders.
Furthermore, you'll need:
- Experience of coaching others
- Knowledge of data science and machine learning
- Experience of using programming and scripting languages, such as Python and Bash
- An understanding of how to synthesise, translate and visualise data and insights for key stakeholders
- Financial services knowledge and the ability to identify wider business impacts, risks and opportunities to make connections across key outputs and processes
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