Assistant Machine Learning Engineer

Job Description

We are a lean team building cloud solutions that users actually get excited about—and we care just as much about how we ship them as what we build: simple, secure, and scalable.

Beyond technical strength, we value engineers who bring ownership and clarity to their day-to-day work—planning effectively, breaking down complexity, asking thoughtful questions, and communicating progress early so there are no surprises.

As an Assistant Machine Learning Engineer you will connect the dots between your work and real outcomes, explain ideas in a clear and simple way, and learn quickly in an empowered environment.

You will report to Product Manager.

What you'll do:

• Deploy and configure Ascend Sandbox environments using CI/CD, ensuring repeatable, scalable and reliable platform setup
• Design, build and maintain data pipelines to support product and analytics use cases on Ascend Sandbox
• Contribute to end-to-end platform and services design, integration and rollout across new markets
• Support and maintain Sandbox platform and services, and drive continuous improvement
• Support product development on top of Ascend platforms

Qualifications

What you'll bring:

• Experience with Azure, main cloud services (Azure blob storage, Virtual machines, networking, Active Directory), Databricks, Azure Data Factory
• Experience with CI/CD process development (Jenkins)
• Experience with infrastructure as a code (Terraform)
• Exposure to Linux
• Good knowledge of OOP principles, data structures, algorithms & design patterns
• Knowledge and appreciation of agile development methodologies and techniques
• 3+ years of working knowledge in Python – preferably both Python's own syntax but also some of its main analytical packages (such as Pandas, Numpy, MatplotLib)
• Basic knowledge of statistics and of measures used for evaluating performance of Machine Learning models, such as precision, recall, etc.
• Basic understanding of Data Science concepts such as overfitting, cross-validation, test-vs-train split, etc.
• Knowledge in managing Databricks or similar platforms, with experience in data management and data processing
• Experience in using PySpark, SparkSQL, Delta Lake, DataFrames, jobs, Model tracking etc., and administration for notebooks and workflow

We will consider any of the following abilities and skills an advantage:

• Experience with containerization of ML models (fastapi)
• Experience with AWS, main cloud services (S3, EC2, Lambda functions, networking) + EKS, Sagemaker, managed elastic search and kafka services
• Experience with Apigee for APIs management
• Experience with SSO integrations (Okta)

Additional Information

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

This is a hybrid remote/in-office role.

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