Machine Learning Engineer
Hang- Full Time
- Senior (5 to 8 years)
Candidates should possess a Bachelor's degree in Computer Science or an equivalent degree, along with at least three years of software development experience. They should have experience with machine learning frameworks and models, with preferred experience utilizing PyTorch, and a strong understanding of statistical analysis and mathematical data manipulation. Proficiency in web technologies such as Java, Python, JavaScript, React/Redux, and Kotlin is required, alongside experience with relational databases, big data, and SQL. Familiarity with GIT, GitFlow, JIRA, Gitlab, and Confluence is also necessary, as is a strong sense of accountability and solution-focused abilities.
The Software ML Engineer will be responsible for defining, developing, testing, analyzing, and delivering technology solutions within Nielsen’s Collections platforms, supporting the measurement of television viewing in over 30 countries. This includes working with web technology, writing unit and integration tests, utilizing best practices for software development and deployment, and troubleshooting functional and technical issues. The role also requires a passion for learning and growing technology skills, as well as contributing to the organization by driving change and demonstrating strong analytical and problem-solving skills.
Global measurement and data analytics provider
Nielsen provides measurement and data analytics services to help businesses understand consumers and markets globally. The company operates through two main divisions: Nielsen Global Media, which offers reliable metrics for the media and advertising industries, and Nielsen Global Connect, which supplies consumer packaged goods manufacturers and retailers with actionable insights about the marketplace. Nielsen combines its proprietary data with other sources to give clients a comprehensive view of current trends and future opportunities. With a presence in over 100 countries, Nielsen aims to support companies in making informed decisions to drive innovation and growth.