Level

Experian

Machine Learning Engineer

Experian is hiring a Machine Learning Engineer in Sofia, Bulgaria. Level rates it ; you can apply on Level.

AI in this role

Develops and maintains predictive models and machine learning pipelines for analytical solutions.

pythonsqlawsazure
nlpmachine-learningpredictive-modelingdata-analysismlopsautomation

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.

As a Machine Learning Engineer you will report to the Trusso Technical Lead and you will join our Analytics CoE in Sofia to help maintain analytical solutions for Experian clients. You will focus on data intelligence, automation of analytical procedures, and the delivery of analytical and machine learning solutions across cloud and on-premises environments.

You will combine machine learning engineering, software development, data analysis, and automation. You will contribute to predictive model development. You will do ad-hoc analysis, write production-level code, support automated testing and deployment, and help improve analytical workflows to improve operational efficiency and speed time-to-market.

You will work with data scientists, product managers, and other teams to create analytical solutions.

What you'll do:

  • Develop solutions, including data analysis, predictive model development, and ad-hoc analysis, delivering accurate and reliable production-level code to meet our requirements.
  • Help develop and maintain machine learning pipelines for data ingestion, transformation, and model training.
  • Integrate communication, collaboration, and automation across the flow of work to improve processes, reduce IT operational costs, and increase speed-to-market.
  • Conduct tests of automated solutions and support reliable delivery of analytical applications.
  • Produce technical documentation and ensure solutions comply with Experian internal best practices and requirements.
  • Conduct code reviews of peers work with a high level of diligence, attention, and proficiency.
  • Help deliver proofs of concept to evaluate analytical and technical approaches.
  • Identify opportunities for automation and contribute to cost/benefit analyses that justify the value of proposed improvements.
  • Work on assigned activities, gathering input from colleagues and management to address issues within the project team.
  • Ensure a clear and full understanding of client and customer requirements and translate those needs into analytical or technical solutions.
  • Understand and balance the varied interests and conflicting needs of partners and communicating it.
  • Maintain positive daily client and customer relationships while supporting successful project delivery.
  • Develop competency and knowledge across software development and analytics, maintaining an understanding of both disciplines.
  • Remain current on recent developments in data assets, analytical methods, and software tools through internal and external training and apply relevant learning to project work.
  • 1+ year technical experience in software development, with the ability to write production-level code in at least one general-purpose programming language, such as Python or C++.
  • Understanding of modern technologies for processing large datasets, including Apache technologies such as Hadoop and Spark, and database technologies such as graph databases and time-series databases.
  • Exposure to natural language processing and other tools for parsing or analysing unstructured data.
  • Comfortable working with cloud technologies such as AWS, Azure, or Google Cloud Platform and virtual environment technologies such as Docker, Kubernetes, and OpenShift.
  • Back-end development skills, including experience working with REST APIs.
  • Familiarity with front-end frameworks such as Angular or React.
  • Understanding of domain products and services and how they are used by clients, with an ability to contribute to business and technical discussions.
  • Advanced degree or equivalent in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or another relevant field.
  • Fluent English

What 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, dental coverage, 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.

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

#LI-Hybrid

This is a hybrid remote/in-office role.

Experian Careers - Creating a better tomorrow together

Experian Careers - Creating a better tomorrow together

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

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 90 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

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

NLPMachine learningPredictive ModelingData AnalysisMLOpsAutomationPythonSQL

Also common in machine learning engineer jobs at this level

Pay

Typical machine learning engineer job
$199k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

  1. What NLP problem have you worked on, and how did you measure whether it actually worked?
  2. Tell me about a project where machine learning was part of your work. What did you do?
  3. Tell me about a project where predictive modeling was part of your work. What did you do?
  4. Tell me about a project where data analysis was part of your work. What did you do?
  5. Tell me about a project where mlops was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: NLP, Machine learning, Predictive Modeling, Data Analysis, and MLOps. 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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