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Philips · 3 months ago

PhD. Co-op – AI Research / Generative AI Engineer – Orlando, FL – January 2026

Orlando

Full-time

Onsite

New Grad

$29/hr - $45/hr

Philips is a health technology company focused on improving healthcare access and quality for everyone. They are seeking a PhD Co-op in AI Research / Generative AI Engineering to work on innovative AI solutions for medical devices, bridging academic research with industrial applications.

B2BConsumer ElectronicsElectronicsLightingWellness

No H1B

U.S. Citizen Only

Responsibilities

Design and Prototype Novel Generative AI Solutions: Take a leading role in the research, design, and implementation of proof-of-concept (PoC) and prototype applications for key systems engineering use cases

Leverage our Modern AI Platform: Work hands-on with our purpose-built AI stack, including: Interacting with and extending the Open-WebUI API gateway. Utilizing Azure OpenAI models (GPT-4o, text-embedding-3-large) via our LiteLLM proxy. Building solutions on top of our Qdrant vector database, designed for terabyte-scale knowledge bases. Deploying and managing services within a Docker containerized environment

Advance the State-of-the-Art in RAG and Agentic Applications: Investigate and apply cutting-edge techniques in Retrieval-Augmented Generation (RAG), including advanced chunking strategies, re-ranking algorithms, and prompt engineering to optimize performance for complex technical and regulatory documents

Help define “What’s Next”: Design and build Agents that can take complex product development objectives, plan and execute to achieve them using a ReAct framework and tools including our RAG API. Contribute to the architecture definition for an MCP server and client tools and UI that allows for a scalable approach to implementing multi-step engineering tasks. Help design and implement the core an Agent Coordinator responsible for task decomposition, planning, and executing multi-step workflows using advanced reasoning

Collaborate and Communicate Findings: Work closely with senior systems engineers and subject matter experts to understand workflow challenges. Present your findings, demo your prototypes, and contribute to the team's strategic direction. There may be opportunities to publish or present your work

Qualification

Natural Language ProcessingLarge Language ModelsPythonRAG pipelinesCloud computingVector databasesCollaborationCommunication

Required

Currently pursuing a PhD in Computer Science, Artificial Intelligence, Computational Linguistics, or a closely related technical field

Demonstrated experience in Natural Language Processing (NLP) and hands-on expertise with Large Language Models (LLMs) and transformer architectures

Strong programming skills in Python and experience with common ML/NLP libraries (e.g., PyTorch, TensorFlow, Hugging Face, scikit-learn)

Solid theoretical understanding and practical experience in designing and building RAG pipelines, including knowledge of vector databases (e.g., Qdrant, Pinecone, FAISS) and embedding models

Familiarity with cloud computing platforms (Microsoft Azure is a strong plus) and their associated AI/ML services

Ability to successfully perform the minimum Physical, Cognitive and Environmental job requirements with or without accommodation