AI / ML Engineer II (P2)

Nielsen Holdings Plc; Hinoba-an; On-site; PHP 5,629,000 - 8,130,000; Full time

Job summary

Nielsen Holdings Plc in the Philippines is seeking a hands-on Machine Learning Engineer to build, train, and deploy end-to-end ML models with autonomy on well-defined projects.

You will collaborate with cross-functional teams, design robust ML pipelines, and deploy on AWS with VPC, EC2, EMR, S3, and EKS, delivering scalable production-grade solutions.

Qualifications

• 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 Spark.
• Experience deploying ML workloads on AWS using VPC, EC2, EMR, S3, and RDS.
• AI experience with modern frameworks and techniques including LLMs or Generative AI.

Responsibilities

• Independently build, train, and deploy ML models for complex projects.
• Provision and manage AWS infrastructure for 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 system architecture.
• Collaborate with business, product, and other engineering teams to translate requirements into specs.
• Write production-ready code and participate in code reviews.
• Mentor interns or junior engineers.

Skills

Python

SQL

Spark

AWS

Airflow

MLflow

LLMs

Generative AI

Kubernetes

VPC

EC2

EMR

S3

RDS

Data processing

Distributed computing

Education

Bachelor's or Master's degree in Engineering/Mathematics/Statistics

Tools

Apache Spark

MLflow

Airflow

Kubernetes (EKS)

Job 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.