Machine Learning Engineer, VP

Posted 20 Days Ago
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Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office
Expert/Leader
Fintech • Payments • Financial Services
The Role
Lead design, deployment, automation, monitoring and maintenance of production ML models and pipelines. Partner with stakeholders to translate prototypes into production, ensure robust model monitoring/retraining, and manage multidisciplinary teams delivering complex ML projects.
Summary Generated by Built In

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
  • 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
  • We're offering this role at vice president level
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 have an academic background in a STEM discipline, like Mathematics, Physics, Engineering or Computer Science. You’ll need overall ten 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.

You’ll also 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

Hours

45

Job Posting Closing Date:

14/08/2026

Skills Required

  • Academic background in a STEM discipline (Mathematics, Physics, Engineering, Computer Science)
  • 10 years of experience with machine learning on large datasets
  • Experience building, testing, supporting and deploying ML models into production using CI/CD tools such as TeamCity and CodeDeploy
  • Experience coaching others and leading teams
  • Proficiency with programming and scripting languages such as Python and relevant libraries
  • Experience with machine learning frameworks such as TensorFlow and PyTorch
  • Experience with cloud platforms (AWS, Google Cloud Platform, or Azure) for deploying ML models
  • Strong understanding of CI/CD pipelines, version control (Git), and containerization (Docker)
  • Knowledge of ML algorithms, MLOps, LLMOps and model evaluation concepts (overfitting, metrics)
  • Good communication skills to engage a wide range of stakeholders

NatWest Group Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NatWest Group and has not been reviewed or approved by NatWest Group.

  • Flexible Benefits A flexible ValueAccount structure with pension and benefit funding allows tailoring of health, protection, lifestyle, and savings options, with unused amounts typically paid as cash. This flexibility supports personalisation of coverage, particularly in Great Britain where the framework is most detailed.
  • Retirement Support Employer-funded pension contributions are provided on top of salary in Great Britain, alongside automatic retirement enrollment and share/save programs. This creates structured long‑term wealth support as part of total reward.
  • Parental & Family Support UK policies outline extended maternity, adoption and equal partner leave on full pay with a phased return, plus paid neonatal care leave. These provisions are positioned as market‑leading and complement broader flexibility resources.

NatWest Group Insights

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The Company
HQ: Edinburgh
40,000 Employees
Year Founded: 1970

What We Do

We’re a business that understands when our customers and people succeed, our communities succeed, and our economy thrives. As part of our purpose, we’re looking at how we can drive change for our communities in enterprise, learning and climate. As one of the leading supporters of UK business, we’re prioritising enterprise as a force of change. We’re focusing on the people and communities who have traditionally faced the highest barriers to entry and figuring out ways to remove these. Learning is also key to our continued growth as a company in an ever changing and increasingly digital world. By setting a dynamic and leading learning culture, our people prosper, and our customers are given the tools to continue to improve their financial capability and confidence. One of the biggest challenges we all face in our future is climate change. That’s why we’ve put it right at the core of our purpose. We want to champion climate solutions with financing and entrepreneurial support, fully embed climate into our culture and decision making, and be climate positive by 2025. We’re committed to using our purpose to break down barriers, drive change and ultimately create a great place to work.

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