Jobs

Machine Learning Engineer - GenAI


Job details
  • Experian
  • London
  • 2 weeks ago
Applications closed

Company Description

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realise their financial goals and help them save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.

We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at www.experianplc.com

Job Description

Grade : D/C

Location: London/Hybrid

The GenAI CoE function consists of teams of Product Managers, ML Engineers and Data Scientists dedicated to building rapid prototypes of new Experian data products, that spearhead the next wave of product innovations using generative AI.

The Machine Learning Engineering team in the CoE facilitates the transition of concepts and proved ideas into products and services that Experian can take to their customers, whether that be businesses or direct to consumers. To do this, we build upon the outcomes of our experiments to meet the product requirements - considering performance, maintainability, and scalability.

Reporting into our Delivery Manager, we are seeking an experienced Senior to Mid-level Developer to deliver machine learning solutions from concept to production-ready solutions, embracing standard industry processes such as Agile, DevOps, version control and model management. You will work with large data sets to build solutions, thinking about the design and architecture of the product and how it can be scaled.

This is a really exciting opportunity for someone who has an interest in the commercial application of machine learning solutions and is keen to discover and introduce new technologies into the team.

Qualifications

  1. Advanced proficiency in Python, with a foundation in OOP, SOLID principles, TDD, and domain driven design.
  2. Experience with prompt engineering.
  3. Experience with one or more additional programming languages (Java, JavaScript, C++, Go, C#) is beneficial.
  4. Experience of machine learning frameworks and toolkits such as sklearn, XGboost, TensorFlow.
  5. Good cloud skills AWS & Azure.
  6. Familiarity with Unix and scripting languages.
  7. Proficient with Docker working in any container orchestrator such as k8s, OpenShift, Docker swarm.

Additional Information

Our uniqueness is that we truly celebrate yours. Experian's culture and people are key differentiators. We take our people agenda very seriously and focus on what truly matters; DEI, work/life balance, development, authenticity, engagement, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's strong people first approach is award winning; Great Place To Work in 24 countries, FORTUNE Best Companies to work and Glassdoor Best Places to Work (globally 4.4 Stars) to name a few. Check out Experian Life on social or our Careers Site to understand why.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is a critical part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

#LI-ST1 #Hybrid

Experian Careers - Creating a better tomorrow together

Find out what it's like to work for Experian by clicking here.

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