Machine Learning Engineer, AVP

Overview

Join our digital revolution in NatWest Digital X

In everything we do, we work to one aim. To make digital experiences which are effortless and secure.

So we organise ourselves around three principles: engineer, protect, and operate. We engineer simple solutions, we protect our customers, and we operate smarter.

Job Description

Our people work differently depending on their jobs and needs. From hybrid working to flexible hours, we have plenty of options that help our people to thrive.

This role is based in India and as such all normal working days must be carried out in India.

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
• We're offering this role at associate vice president level
  
  
  

What you’ll do

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
  
  
  

The skills you’ll need

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 overall eight years of 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
• Experience of using programming and scripting languages, such as Python and relevent libraries along with machine learning framework such as Tensorflow and Pytorch
• Experience with AWS, Google cloud platform, or Azure for deploying machine learning models
• Strong understanding of CI/CD pipelines, version control such Git, and containerization such as Docker
• Knowledge of various machine learning algorithms, MLOps,LLMOps and familiarity with concepts such as overfitting and model evaluation metrics