Data Scientist - Generative AI

Job Title

Job Description

Key Responsibilities

We are seeking a highly skilled Data Scientist with Generative AI expertise to join our team. In this role, you will develop, fine-tune, and optimize generative AI models to drive innovation across various applications, including text, image, audio, and video generation. You will collaborate with cross-functional teams, including machine learning engineers, software developers, and product managers, to create cutting-edge AI solutions.  

Must Have

• Proficient in Python

• Understanding of the Pytorch and TensorFlow frameworks

• Understanding the NLP techniques and text processing tools such as NLTK, Gensim etc.

• Proficient with LLM models from HuggingFace for different text processing tasks

• Proficient with data handling capabilities and querying from SQL/No-SQL databases

• Understanding of the vision problems that can be solved using generative AI models

Good to Have

• Experience with prompt engineering techniques and leverage best practices with LLM technology 

• Develop and Optimize Generative AI Models – Design, train, and fine-tune models such as GPT, Stable Diffusion, StyleGAN, and LLaMA for real-world applications.  

• Data Preparation & Engineering – Gather, clean, and preprocess large-scale datasets for training and evaluation of generative models.  

• Experimentation & Model Evaluation – Conduct A/B testing and assess model performance using quantitative metrics (e.g., FID, BLEU, perplexity, ROUGE etc.).  

• Research & Innovation – Stay updated with the latest advancements in generative AI, deep learning, and large language models (LLMs).  

• Deployment & Scaling – Work with ML engineers to deploy models into production environments using cloud platforms (AWS, Azure) and frameworks like TensorFlow, PyTorch, and Hugging Face.  

• Collaboration & Communication – Work closely with cross-functional teams to integrate AI solutions into business processes and applications.

You're the right fit if:

• Bachelor’s or master’s degree in computer science, AI, Data Science, Machine Learning, or a related field.

• 3+ years of experience in machine learning, deep learning, or AI research, with at least 1 year of hands-on experience in generative AI.  

• Strong proficiency in Python and ML frameworks like TensorFlow, PyTorch, or JAX.  

• Experience working with LLMs, diffusion models, GANs, VAEs, or transformers.  

• Knowledge of natural language processing (NLP), computer vision, or multimodal AI applications.  

• Familiarity with prompt engineering, fine-tuning, and RLHF (Reinforcement Learning from Human Feedback).  

• Experience in cloud-based AI solutions and working with APIs (e.g., OpenAI, Hugging Face, Stability AI).  

• Strong problem-solving skills and the ability to work in a fast-paced, research-driven environment.  

• Experience with vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG).  

• Hands-on experience with MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes).  

• Understanding of ethical AI and bias mitigation in generative models.  

• Strong publication record or contributions to open-source AI projects.

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 commitment to diversity and inclusion here.

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