Machine Learning Engineer

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 Be Doing:
Develop analytical and machine learning solutions, including data analysis, predictive modelling, proof of concepts and production-ready code.
Build and support machine learning pipelines, covering data ingestion, transformation, model training, testing and reliable delivery of analytical applications.
Promote automation and process improvements, identifying opportunities to improve efficiency, reduce operational effort and increase speed-to-market.
Contribute to software engineering best practices, including code reviews, technical documentation and compliance with Experian standards.
Work with partners, clients and project teams to understand requirements, manage priorities and translate needs into analytical or technical solutions.
Develop technical expertise, staying up to date with software development, analytics, data assets, tools and latest technologies through ongoing learning and application.
What we're looking for:
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++.
Experience working with data and backend systems, including large datasets, REST APIs and modern data processing technologies (e.g. Hadoop, Spark, graph or time-series databases), exposure to front-end frameworks such as Angular or React
Knowledge of cloud and infrastructure technologies, such as Amazon Web Services, Azure or GCP, and exposure to Docker, Kubernetes, OpenShift or similar tools.
Proficiency in English, with the ability to understand products and services, contribute to technical discussions and collaborate with stakeholders and clients.
Exposure to Machine Learning and NLP concepts, including working with unstructured data, and a relevant degree in Computer Science, Machine Learning, Statistics, Applied Mathematics, Engineering or a related field.

Employment type
Full-time

Work arrangement
No