Level

Experian

Machine Learning Engineer

AI in this role

prompt-engineeringragai-evaluation

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.

Our Experian Software Solution's Analytics Services Team supports advanced analytic and generative AI products for decisioning, analytics, fraud, and identity globally.

As a Machine Learning Engineer, you will design, build, and deploy cutting‑edge machine learning and generative AI solutions at scale. You will combine deep data science expertise with ML engineering and data engineering capabilities to deliver production‑ready models, prototypes, and platform capabilities. You will also partner with cross‑functional teams to support new global product launches, client implementations, and early client adoption. You will report to the Director of Data Science and Gen AI.

What you'll do:

  • You will partner with data scientists and then expand to cover packaging and productization of additional analytics solutions.
  • You would deliver the last mile of those innovations, ensuring that production code is executed within the Ascend platform and software that Experian delivers to clients.
  • Collaborate with Engineering, Research, and Data Science teams in the design and implementation of Machine Learning, Dashboarding, Ad Hoc Analysis and AI applications in a cloud-native big data (AWS) computing platform.
  • Partner with Leaders, Analytic Consultants, Engineers, Account Executives, Product Managers, and external partners to bring new solutions to market that provide impact to Experian's broad client base.
  • Craft advanced machine learning analytical solutions and prototypes to extract insights from diverse structured and unstructured data sources. Articulate model processes and outcomes, documenting and presenting findings and performance metrics, and translating complex findings into relevant insights.
  • Use Gen AI and model development tools to develop new models and to prototype and deploy new generative capabilities, including prompt engineering, fine‑tuning, RAG, and model evaluation frameworks.
  • Develop production-quality code following software engineering best practices, including modular design, version control, code reviews, and automated testing, ensuring reliability and reproducibility.
  • Communicate model methodologies, assumptions, performance, and trade-offs to both technical and non‑technical stakeholders. Deliver clear documentation and translate complex concepts into insights.
  • Design and implement advanced algorithms to solve complex challenges, exploring methods across supervised, unsupervised, deep learning, graph analytics, anomaly detection, and reinforcement learning.
  • Contribute to feature and platform evolution by gathering feedback from clients and our teams, helping prioritize enhancements across Experian's ML and AI ecosystem.

What you'll bring:

  • 4+ years of experience in AI, data science, or predictive modeling, with a track record for managing complex, hands-on analytical technology, innovation, and client-focused projects;
  • Advanced degree in Machine Learning, Data Science, AI, Computer Science, or a related quantitative field;
  • Statistical modeling proficiency in at least one programming language, with coding skills in Python,and proficiency with distributed computing frameworks (AWS). Experience with large data analysis using Spark (pySpark preferred) and model development using Python or SAS;
  • Experience applying Generative AI-based tools and rapid prototyping of new concepts;
  • Having some background in model risk management / governance processes, regulatory requirements, and LLM advances.

You will get:

  • Personal Development - career pathway for professional growth supported by learning and development programs and unlimited access to online educational training courses, learning materials and books.
  • Work environment - excellent work conditions with friendly environment, recognized team spirit, and fun and quality recreation time.
  • Social benefit package including life insurance, food vouchers, additional health insurance, monthly flex allowance and internet coverage, corporate discounts, marriage and childbirth / adoption allowance, Multisport card, Sharesave plan, Employee assistance program, а birthday gift and many other benefits!
  • Work-life balance - 25 days paid vacation, 1 additional day off for your birthday and extra 3 paid days for participation in Social responsibility event.
  • Opportunity for Flexible working hours and Home Office.

 

Experian is an Equal opportunity employer. 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-Hybrid

Our uniqueness is that we celebrate yours. Experian's people first, inclusive and purpose driven culture is multi award-winning; World's Best Workplaces™ 2025 (Fortune Global Top 25), Great Place To Work™ in 26 countries to name a few. Check out Experian Life on social or explore our Careers Site to understand why. Experian is also proud to be an Equal Opportunity and Affirmative Action employer. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

Recruitment Fraud Awareness - Experian's recruitment process is conducted only through authorised channels. Recruitment communications will only be sent from an @experian.com email address. Experian will never ask candidates to make any payment as part of an application, interview, assessment, onboarding, or recruitment process. To apply for roles or verify opportunities, please visit experian.com/careers.

Experian Careers - Creating a better tomorrow together

Find out what its like to work for Experian by clicking here

How we rate this

Machine Learning Engineer at Experian rates 94 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Prompt EngineeringRAGAI Evaluation

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you design a retrieval step so the model answers from real data instead of guessing?
  3. How do you decide that one model's output is better than another's for a given task?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: Prompt Engineering, RAG, and AI Evaluation. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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