Machine Learning Engineer

Nielsen; Gurugram District; On-site; INR 2,400,000 - 4,200,000; Full time

Job summary

Nielsen is seeking a Machine Learning Engineer to build and deploy end-to-end ML models with autonomy on well-defined projects. You will translate business needs into scalable ML solutions and deepen your expertise through complex challenges.

Responsibilities include building pipelines, contributing to architecture discussions, collaborating across teams, and mentoring junior engineers. The role emphasizes production-grade code and best practices.

Qualifications

• Bachelor's or Master's degree in a relevant field.
• 4–6 years of professional ML engineering experience.
• Proven experience in building and deploying ML models in production.
• Strong Python and SQL skills with distributed computing experience.

Responsibilities

• Build, train, and deploy end-to-end ML models.
• Design robust ML pipelines from data processing to serving.
• Contribute to system architecture and best practices.
• Collaborate with business, product and engineering teams to translate requirements.
• Write production-ready code and participate in code reviews.
• Mentor interns or junior engineers.

Skills

Python

SQL

Spark

Airflow

MLflow

Deep learning

Classification models

Regression models

Anomaly detection

Boosted models

Simulation problems

Education

Bachelor's or Master's degree

Tools

Airflow

MLflow

Spark

Job description

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.

Requirements

• Bachelor's or Master's degree in Engineering, Mathematics, Statistics, or a related field.
• 4-6 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).
• 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.