AI/ML Data Engineer- Sales Forecasting

Philips; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Philips data science team seeks an AI/ML Data Engineer- Sales Forecasting to build scalable data pipelines and deploy AI models powering Philips’ smart consumer products. You will work with real-time sensor data, user feedback, and behavioral patterns to deliver personalized and secure health experiences.

You will collaborate with BU, COE and cloud teams to integrate AI into consumer-facing apps and platforms, and implement SDLC practices for continuous delivery while ensuring data privacy and

Qualifications

• Bachelor’s or Master’s in Computer Science, Data Engineering, or related field.
• 3–6 years of experience in data engineering and AI development, preferably in consumer tech.
• Strong proficiency in Python, fine-tuning LLMs, TensorFlow/PyTorch, and SQL; solid experience with cloud platforms (Azure/GCP), cloud-native development, and deploying AI workloads using containers and Kubernetes.
• Practical experience in modern full-stack development using Next.js, Node.js, and React for building AI-driven user interfaces and applications.
• Familiarity with consumer data privacy standards (GDPR, CCPA).

Responsibilities

• Build and deploy AI models for personalization, anomaly detection, and predictive health insights.
• Collaborate with BU, COE and cloud teams to integrate AI into consumer-facing apps, Business processes and platforms.
• Implement SDLC practices for continuous delivery and monitoring of AI models.
• Ensure data privacy and compliance with consumer data protection regulations.

Skills

Python

Fine-tuning LLMs

TensorFlow

PyTorch

SQL

Cloud platforms (Azure/GCP)

Containerization & Kubernetes

Data privacy (GDPR/CCPA)

Education

Bachelor’s or Master’s in Computer Science, Data Engineering, or related field

Tools

Next.js

Node.js

React

Docker

Kubernetes

Job description

Your Role

As a Data & AI Engineer in the Personal Health division, you will build scalable data pipelines and deploy AI models that power Philips’ smart consumer products. You will work with real-time sensor data, user feedback, and behavioral patterns to deliver personalized and secure health experiences.

• Build and deploy AI models for personalization, anomaly detection, and predictive health insights.
• Collaborate with BU, COE and cloud teams to integrate AI into consumer-facing apps, Business processes and platforms.
• Implement SDLC practices for continuous delivery and monitoring of AI models.
• Ensure data privacy and compliance with consumer data protection regulations.

Job Title

AI/ML Data Engineer- Sales Forecasting

You're The Right Fit If

• Bachelor’s or Master’s in Computer Science, Data Engineering, or related field.
• 3–6 years of experience in data engineering and AI development, preferably in consumer tech.
• Strong proficiency in Python, fine-tuning LLMs, TensorFlow/PyTorch, and SQL; solid experience with cloud platforms (Azure/GCP), cloud-native development, and deploying AI workloads using containers and Kubernetes.
• Practical experience in modern full-stack development using Next.js, Node.js, and React for building AI-driven user interfaces and applications.
• Familiarity with consumer data privacy standards (GDPR, CCPA).

How We Work Together

We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week.

Onsite roles require full-time presence in the company’s facilities.

Field roles are most effectively done outside of the company’s main facilities, generally at the customers’ or suppliers’ locations.

This role is an office role.

About Philips

We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others.

• Learn more about our business.
• Discover our rich and exciting history.
• Learn more about our purpose.