Job Responsibilities:
Someone who can design, build, and fine-tune Generative AI models (LLMs, vision-language models, diffusion models) for product use cases
Hands on expertise in Large Language Models and prompt engineering
RAG architectures, vector databases, embeddings
Experiment tracking tools (MLflow, Weights & Biases)
Traditional ML/DL techniques
Work with structured and unstructured datasets (images, text)
Collaborate with engineering teams to integrate AI models into production systems and embedded/edge environments
Minimum required Education:
Bachelor's / Master's Degree in Information Management, Information Systems, Computer Science, Data Analytics, Data Science or equivalent.
Minimum required Experience:
Minimum 7 years of experience with Bachelor's OR Minimum 5 years of experience with Master's in areas such as Data Analytics, Data Modeling or equivalent.
Preferred Skills:
• Data Science
• Data Analysis & Interpretation
• Data Designing
• Python
• GenAI frameworks(LangChain, LangGraph)
• Vector Databases
• Machine Learning Engineering Fundamentals
• Statistical Methods
• Statistical Programming Software
• Research & Analysis
• Structured Query Language (SQL)
• Regulatory Compliance
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.
Indicate if this role is an office/field/onsite 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.
If you’re 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.
Skills Required
- Bachelor's degree in Information Management, Information Systems, Computer Science, Data Analytics, Data Science, or equivalent
- At least 7 years of experience with a bachelor's degree in data analytics, data modeling, or equivalent
- At least 5 years of experience with a master's degree in data analytics, data modeling, or equivalent
- Data science experience
- Data analysis and interpretation experience
- Data design experience
- Python
- Generative AI frameworks, including LangChain and LangGraph
- Vector database experience
- Machine learning engineering fundamentals
- Statistical methods and statistical programming software
- Research and analysis experience
- SQL
- Regulatory compliance experience
Philips Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Philips and has not been reviewed or approved by Philips.
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Retirement Support — Retirement support is positioned as a standout, including a strong 401(k) match (often described at 7%) alongside pensions in some contexts.
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Flexible Benefits — Flexible benefits are emphasized through choice in health insurance options and a broad “Total Rewards” approach that combines compensation, health and wellness, and work-life support.
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Leave & Time Off Breadth — Leave and time off breadth appears strong, with generous paid time off and policies covering parental leave, caregiving responsibilities, volunteering, and family medical leave.
Philips Insights
What We Do
As a leading health technology company, it is our purpose to improve people’s health and well-being through meaningful innovation. Our goal is to improve 2.5 billion lives per year by 2030. We're always looking for ways to make life better – not only for our customers, but also for everyone working here. That's why we're taking steps to create an environment where we all acknowledge and embrace our differences and uniqueness and listen to and value each other's views. When people feel cared for and listened to, they bring their best qualities to work, leading to better collaboration, communication, innovation and success.
