About the Role:

Philips is seeking a highly skilled Data Scientist with expertise in Generative AI to join its innovative team. In this role, you will be responsible for developing, fine-tuning, and optimizing generative AI models that drive innovation across multiple modalities, including text, image, audio, and video generation. This position offers the opportunity to work closely with machine learning engineers, software developers, and product managers to design and deploy cutting-edge AI solutions into real-world applications.

Key Responsibilities:

• Develop and optimize generative AI models such as GPT, Stable Diffusion, StyleGAN, and LLaMA for real-world use cases.
• Gather, clean, and preprocess large-scale datasets for training and evaluation of generative models.
• Conduct experimentation and model evaluation using metrics like FID, BLEU, perplexity, ROUGE, etc.
• Stay updated with the latest advancements in generative AI, deep learning, and large language models (LLMs).
• Collaborate with ML engineers to deploy models into production environments using cloud platforms such as AWS and Azure, along with frameworks like TensorFlow, PyTorch, and Hugging Face.
• Integrate AI solutions into business processes and applications by working closely with cross-functional teams.
• Apply prompt engineering techniques and leverage best practices in working with LLM technology.

Key Technical Skills:

Python, PyTorch, TensorFlow, NLP, NLTK, Gensim, Hugging Face LLMs, SQL, NoSQL, GANs, Diffusion Models, Transformers, Prompt Engineering, Cloud Platforms (AWS, Azure), APIs (OpenAI, Hugging Face, Stability AI), Vector Databases (FAISS, Pinecone), MLflow, Kubeflow, Docker, Kubernetes

Requirements:

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Machine Learning, or related field.
• Minimum of 3 years of experience in machine learning, deep learning, or AI research, with at least 1 year specifically in generative AI.
• Strong proficiency in Python and familiarity with 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 reinforcement learning from human feedback (RLHF).
• Experience deploying AI solutions on cloud platforms and working with related APIs.
• Experience with vector databases such as FAISS or Pinecone, and retrieval-augmented generation (RAG) techniques.
• Hands-on experience with MLOps tools like MLflow, Kubeflow, Docker, and Kubernetes.
• Understanding of ethical AI practices and bias mitigation in generative models.
• Strong problem-solving skills and ability to work in a fast-paced, research-driven environment.
• Strong publication record or contributions to open-source AI projects are a plus.

Working Model:

Philips values in-person collaboration. Office-based teams are expected to work onsite at least 3 days per week. This role is categorized as an onsite position, requiring full-time presence in the company’s facilities.

About Philips:

Philips is a health technology company dedicated to improving lives through meaningful innovation. With a mission centered around ensuring everyone has access to quality healthcare, Philips aims to create a significant impact on global health outcomes. Employees at Philips contribute to building a healthier world through their work, supported by a culture focused on care and impact.