Data & AI Engineer

Job Title

Job Description

Data & AI Engineer

In this role you are part of

MR Service Innovation is building a new Digital & AI team with one mission: keep MRI systems scanning. Every hour an MRI system is down patients wait. Our team applies AI across the full service lifecycle from detecting issues before they cause downtime to resolving cases remotely to protecting service margins as part of our multi-year Autonomous MR journey: a graduated maturity path from Detect to Self-Heal to Predict to Autonomous service.

As a Data & AI Engineer you will build and productionise the AI solutions behind this journey: predictive models that flag failures before they happen GenAI assistants that help field and remote service engineers resolve cases faster and analytics that protect contract revenue and service profitability. You will work with real service data at scale over 100K historical service and machine-log cases and see your work deployed to a global installed base of medical imaging systems.

This is a ground-floor opportunity on a newly formed team: high ownership direct visibility to business leadership and a global working environment spanning India the Netherlands and North America.

Your Role:

• Design develop and deploy production-grade Data and AI solutions across the MR service AI portfolio including predictive failure and remote-resolution models AI-driven parts recommendation root-cause analytics for rework reduction and GenAI applications for contract and entitlement analytics.
• Build and maintain robust data pipelines and data models over service datasets (ITSM cases remote diagnostics/machine logs parts and contract data) ensuring reliable secure high-quality inputs for AI applications.
• Develop integrate and operationalise ML models LLMs Retrieval-Augmented Generation (RAG) pipelines and agentic AI workflows into service tools used by field service engineers and remote service engineers worldwide.
• Take POCs to MVP & productization: harden prototypes (including those built with external AI partners) into validated monitored supportable enterprise solutions.
• Implement AI engineering best practices MLOps/LLMOps CI/CD automated testing monitoring model versioning and governance appropriate to a regulated healthcare environment.
• Develop APIs microservices and cloud-native AI services for scalable deployment across enterprise and service platforms.
• Monitor model performance in the field; retrain and continuously optimise for accuracy latency cost and reliability against measurable service outcomes (system uptime time-to-resolution first-time-right).
• Embed Responsible AI by design: data privacy security explainability auditability and compliance requirements consistent with MedTech and Philips AI governance standards.
• Collaborate closely with Data Scientists System Architects Service Information Architects Product Owners and external delivery partners to translate service business problems into engineered solutions.
• Evaluate emerging AI technologies and frameworks; contribute to code reviews documentation knowledge sharing and the engineering standards of a growing team.

What Makes This Role Different

• Mission with a heartbeat: your models directly reduce MRI downtime that means faster diagnosis for patients not just dashboards.
• Full lifecycle exposure: upstream commercial analytics (contracts entitlements pricing) and downstream operational AI (prediction resolution parts) in one portfolio.
• Real data real scale: validated service case data across a global installed base you build on evidence not toy datasets.
• Builders seat: a newly carved-out team where engineering standards tooling choices and ways of working are still being shaped by you.

Youre the Right Fit If:

Minimum Education

Bachelors or Masters Degree in Computer Science Artificial Intelligence Data Science Information Technology Software Engineering Statistics Mathematics or a related discipline.

Minimum Experience

• Bachelors Degree: 3-6 years of experience in Data Engineering AI Engineering Machine Learning Engineering Software Engineering or related fields.
• OR Vocational/Equivalent Qualification: Minimum 4 years of relevant experience in Data Engineering AI Engineering Analytics Machine Learning or Software Development.

Preferred Qualifications

• Experience with Azure AI Services Azure Machine Learning Microsoft Fabric or Amazon Bedrock (including model orchestration agents and knowledge bases on Bedrock).
• Experience taking Generative AI or agentic AI applications from POC to production in an enterprise setting.
• Exposure to healthcare MedTech or other regulated industries; familiarity with medical device service operations IoT/remote diagnostics data or field service workflows is a strong plus.
• Knowledge of Responsible AI AI governance cybersecurity and data privacy practices (e.g. GDPR healthcare data handling).
• Comfort working in a globally distributed remote-first team across time zones (India Europe North America).
• Strong problem-solving skills with excellent collaboration and communication abilities able to work directly with service domain experts and translate their knowledge into AI solutions.

You will stand out if you also have:

Technical Skills

• Programming: Python (preferred) SQL
• Data Engineering: ETL/ELT data pipelines data modelling for structured and unstructured service data (logs case notes documents)
• Machine Learning: Scikit-learn TensorFlow or PyTorch; experience with time-series classification and NLP on operational data is a plus
• Generative AI: LLMs prompt engineering RAG vector databases agentic AI frameworks; experience with managed GenAI platforms such as Azure OpenAI Service or Amazon Bedrock
• Cloud Platforms: Azure (preferred) AWS or GCP
• MLOps/LLMOps: MLflow Docker Kubernetes GitHub Actions/Azure DevOps CI/CD
• Databases: SQL NoSQL vector databases
• API Development: REST APIs FastAPI or similar frameworks
• Version Control: Git

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 companys facilities.
• Field roles are most effectively done outside of the companys main facilities generally at the customers or suppliers locations.
• This role is an office-based role.
  

About Philips:
We are a health technology company. We built our entire company around the belief that every human matters and we wont 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.
If youre interested in this role and have many but not all of the experiences needed we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our culture of impact with care here.

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