Data Scientist, Generative AI Engineer

Job Description

In this role, we are seeking an applied Data Scientist with hands-on expertise in Generative AI and Machine Learning Engineering to join our team. In this role, you will design and build innovative and ethically responsible Generative AI solutions that effectively address real-world problems, balancing technical feasibility with user needs and business impact. Working at the intersection of natural language processing and machine learning, you will contribute to developing AI solutions that directly impact patient outcomes and Philips' growth in the healthcare sector.

Your role:

• Design, train, and evaluate NLP and LLM-based solutions for various use cases, including retrieval-augmented generation (RAG), information retrieval & search, chatbots, structured information extraction and named entity recognition, text generation, summarization, and more
• Clean, preprocess, and curate data for evaluation, fine-tuning, and training
• Work closely with stakeholders across the organization to understand business needs, formulate problems, and deliver data-driven insights
• Keep up the latest advancements in generative AI research and integrate new techniques into the development process

You are fit if:

• You hold a Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field
• You have at least three years of hands-on experience developing NLP and ML/DL solutions in a professional or enterprise environment
• You are proficient in Python and relevant libraries for data science and deep learning (e.g., NumPy, Pandas, TensorFlow, PyTorch)
• You have a strong understanding of classic NLP and LLM-based approaches and hands-on experience with LLMs, such as RAG, prompt engineering, data synthesis, automatic evaluation, and fine-tuning
• Hands-on experience building and then iteratively refining model pipelines end-to-end, from data curation to evaluation
• Strong analytical and problem-solving skills, with attention to detail, round out your profile

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-based role.