Nielsen
Machine Learning Engineer (MLE-3)
Job description
About the Role:
As a Machine Learning Engineer at this level, you will be a key contributor to our team,
responsible for building and deploying end-to-end machine learning models. You will work with a
degree of autonomy on well-defined projects, translating business needs into functional and
scalable ML solutions. This role is perfect for hands-on ML Engineers looking to deepen their
expertise and take on more complex challenges.
Responsibilities
● Independently build, train, and deploy machine learning models for complex projects.
● Design and maintain robust, end-to-end ML pipelines, from data processing to model serving.
● Contribute to technical design discussions and provide input on system architecture and best practices.
● Collaborate with business, product, and other engineering teams to understand requirements and translate them into technical specifications.
● Write high-quality, production-ready code and participate in code reviews to maintain our standards of excellence.
● Mentor interns or junior engineers, sharing your knowledge and expertise.
● Bachelor's or Master's degree in Engineering, Mathematics, Statistics, or a related field.
● 3-6 years of professional experience in machine learning engineering.
● Proven experience in building and deploying ML models in a production environment.
● Strong proficiency in Python, SQL, and experience with a distributed computing framework (e.g., Spark).
● Data Analytics Experience: Strong background in data analytics, including statistical analysis, data visualization, and reporting to derive business insights.
● AI Experience: Practical, hands-on experience with modern AI frameworks and techniques, including LLMs or Generative AI applications.
● Familiarity with workflow orchestration tools (e.g., Airflow) and ML platforms (e.g., MLflow) is preferred.
● Knowledge of classification models, regression models, anomaly detection, boosted models, deep learning, and simulation problems, particularly with large datasets.
● Strong problem-solving skills and the ability to work independently on projects.
