3 days ago
Bengaluru, IndiaMid Level
Responsibilities
- Build, train, and deploy machine learning models for complex projects.
- Provision, configure, and manage AWS infrastructure supporting ML training and deployment pipelines.
- Design and maintain end-to-end ML pipelines from data processing through model serving.
- Contribute to technical design discussions, system architecture, and engineering best practices.
- Collaborate with business, product, and engineering teams to translate requirements into technical specifications.
- Write production-ready code and participate in code reviews.
- Mentor interns or junior engineers.
Requirements
- Bachelor's or Master's degree in Engineering, Mathematics, Statistics, or a related field.
- 3–6 years of professional experience in machine learning engineering.
- Production experience building and deploying machine learning models.
- Strong proficiency in Python and SQL, plus experience with a distributed computing framework such as Spark.
- Practical experience managing and deploying ML workloads on AWS using VPC, EC2, EMR, RDS, S3, and EKS.
- Hands-on experience with modern AI frameworks and techniques, including LLMs or Generative AI applications.
- Familiarity with workflow orchestration tools such as Airflow and ML platforms such as MLflow is preferred.
- Knowledge of classification, regression, anomaly detection, boosted models, deep learning, and simulation problems, particularly with large datasets.
- Strong problem-solving skills and ability to work independently.
Tech Stack
Categories
About Nielsen
Nielsen shapes the world’s media and content as a global leader in audience insights, data and analytics. Through our understanding of people and their behaviors across all channels and platforms, we empower our clients with independent and actionable intelligence so they can connect and engage with their audiences—now and into the future. Nielsen operates around the world in more than 55 countries. Learn more at http://nlsn.co/6006JMfty and connect with us on social media (LinkedIn, Twitter, Facebook and Instagram).