Machine Learning Engineer

Nielsen; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Nielsen is looking for a Machine Learning Engineer in Bengaluru who will lead the design and development of scalable machine learning systems. With over 6 years of experience, the ideal candidate will optimize data pipelines, mentor team members, and make key design decisions. This hands-on role requires proficiency in Python and SQL, and experience with ML concepts and MLOps. You'll play a critical role in powering intelligent products and fostering a learning-focused team environment.

Qualifications

• 6+ years of professional experience in machine learning.
• Proven track record of deploying production machine learning systems.
• Deep expertise in ML concepts and techniques.

Responsibilities

• Own the complete lifecycle of machine learning systems.
• Make key architectural and design decisions.
• Mentor junior engineers.

Skills

Python

SQL

Machine Learning

Data Engineering

MLOps

Apache Spark

Airflow

Education

Master's or Bachelor's degree in Engineering, Mathematics, Statistics, or a related field

Job description

As a Machine Learning Engineer, you will take a leading role in designing and building the end-to-end systems that power intelligent products at Nielsen. You will own complex projects from conception to deployment, making critical design and architectural decisions. This is a high-impact role for a hands‑on engineer who can handle ambiguity, mentor others, and deliver robust, scalable ML solutions.

Responsibilities

• Own the complete lifecycle of machine learning systems, including problem formulation, data pipeline design, model development, deployment, and monitoring.
• Make key architectural and design decisions to ensure our ML systems are scalable, reliable, and efficient.
• Navigate project requirements, create clear plans of action, and define technical roadmaps.
• Optimize complex data pipelines and ML models for performance.
• Mentor junior engineers on the team, fostering their growth and ensuring high technical standards.
• Act as the technical point of contact for your projects, managing communication with product managers and other stakeholders.
• Cultivate a team environment focused on continuous learning, where innovative audience measurement methodologies are developed and refined through collaborative effort.

Requirements

• Master's or Bachelor's degree in Engineering, Mathematics, Statistics, or a related field.
• 6+ years of professional experience, with a proven track record of owning and shipping production machine learning systems.
• Deep expertise in classification models, regression models, anomaly detection, boosted models, deep learning, and simulation problems, particularly with large datasets.
• Deep expertise in ML concepts, data engineering, and MLOps practices.
• Proficiency in Python and SQL.
• Must have deployed E2E ML systems by automating training and inference pipelines.
• Hands‑on experience with distributed computing frameworks like Apache Spark.
• Experience with workflow orchestration tools (e. g., Airflow) and MLOps.