AI / ML Engineer II (P2)

Nielsen; Bengaluru; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Nielsen Bengaluru is seeking an experienced Machine Learning Engineer to design, train, and deploy end-to-end ML models at scale. You will translate business needs into robust ML solutions and work with autonomy on well-defined projects.

The role requires strong Python and SQL skills, AWS experience (EC2, S3, EMR), and familiarity with Spark. You will collaborate with cross-functional teams, review code, and mentor junior engineers as needed.

Qualifications

• 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.

Responsibilities

• Independently build, train, and deploy machine learning models for complex projects.
• Provision, configure, and manage core AWS infrastructure supporting ML training and deployment pipelines.
• Design and maintain end-to-end ML pipelines from data processing to model serving.
• Contribute to technical design discussions and provide input on system architecture.

Skills

Machine learning

Python

SQL

Distributed computing

Model deployment

LLMs / Generative AI

Code reviews

Independent work

Education

Bachelor's or Master's in Engineering/Math/CS

Tools

AWS

Spark

Kubernetes

MLflow

Airflow

EMR

S3

Job description

Company Description

At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future.

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.
• Provision, configure, and manage core AWS infrastructure supporting ML training and deployment pipelines - utilizing VPC for networking, EC2 and EKS for compute and Kubernetes container orchestration, EMR for big data processing, S3 for artifact and data storage, and RDS for relational database management.
• 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.

Qualifications

Basic Qualifications

• 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).
• Practical experience managing and deploying ML workloads on AWS using VPC, EC2, EMR, RDS, S3, and EKS.
• 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.

Additional Information

Please be aware that job-seekers may be at risk of targeting by scammers seeking personal data or money. Nielsen recruiters will only contact you through official job boards, LinkedIn, or email with a nielsen.com domain. Be cautious of any outreach claiming to be from Nielsen via other messaging platforms or personal email addresses. Always verify that email communications come from an @nielsen.com address. If you're unsure about the authenticity of a job offer or communication, please contact Nielsen directly through our official website or verified social media channels.