3 months ago
Bengaluru, IndiaMid Level / Senior
Responsibilities
- Own the complete lifecycle of machine learning systems, including problem formulation, data pipeline design, model development, deployment, and monitoring.
- Make architectural and design decisions to ensure ML systems are scalable, reliable, and efficient.
- Create project plans, define technical roadmaps, and navigate project requirements.
- Optimize complex data pipelines and machine learning models for performance.
- Mentor junior engineers and maintain high technical standards.
- Serve as the technical point of contact for projects and coordinate with product managers and stakeholders.
- Collaborate on innovative audience-measurement methodologies and foster continuous learning.
Requirements
- Master’s or bachelor’s degree in engineering, mathematics, statistics, or a related field.
- Proven experience owning and shipping production machine learning systems.
- Deep expertise in classification, regression, anomaly detection, boosted models, deep learning, and simulation problems involving large datasets.
- Deep expertise in ML concepts, data engineering, and MLOps practices.
- Proficiency in Python and SQL.
- Experience deploying end-to-end ML systems by automating training and inference pipelines.
- Hands-on experience with distributed computing frameworks such as Apache Spark.
- Experience with workflow orchestration tools such as Airflow.
About Nielsen
Nielsen provides audience measurement and analytics that quantify who watches, listens, and buys across TV, digital, radio, and streaming. It sells ratings, cross-platform datasets, and advertising effectiveness tools to media owners, advertisers, and agencies on subscription and consulting agreements. Founded in 1923 and headquartered in New York, it operates in 55+ countries and is known for U.S. TV ratings.