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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 techniquesu00A0
Work with structured and unstructured datasets (images, text)
Collaborate with engineering teams to integrate AI models into production systems and embedded/edge environments
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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:
u2022 Data Science
u2022 Data Analysis & Interpretation
u2022 Data Designing
u2022 Python
u2022 GenAI frameworks(LangChain, LangGraph)
u2022 Vector Databases
u2022 Machine Learning Engineering Fundamentals
u2022 Statistical Methods
u2022 Statistical Programming Software
u2022 Research & Analysis
u2022 Structured Query Language (SQL)
u2022 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 companyu2019s facilities.
Field roles are most effectively done outside of the companyu2019s main facilities, generally at the customersu2019 or suppliersu2019 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.
u2022 Learn more about .
u2022 Discover .
u2022 Learn more about .
If youu2019re 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 .
Job ID: 150534995
Skills:
Python, LangChain, Weights Biases, Statistical Programming Software, embeddings, Research Analysis, Structured Query Language SQL, vector databases, DL techniques, MLflow, Traditional ML, Machine Learning Engineering Fundamentals, Statistical Methods, prompt engineering, LangGraph, GenAI frameworks, Large Language Models, RAG architectures
Skills:
Azure, Ml, AWS, Pytorch, Tensorflow, Python, Kubernetes, Gcp, MLops, Llm, scikit-learn, GenAI
Skills:
Python, LangChain, Weights Biases, Statistical Programming Software, embeddings, images, Research Analysis, Structured Query Language SQL, DL techniques, vector databases, MLflow, Traditional ML, Statistical Methods, Machine Learning Engineering Fundamentals, prompt engineering, LangGraph, unstructured datasets, text, Regulatory Compliance, GenAI frameworks, Large Language Models, structured datasets, RAG architectures
Skills:
vectorization , language translation , tokenization , Keras, Deep Learning, Tensorflow, Hadoop, AWS, Pytorch, Azure, Sentiment Analysis, Spark, Lemmatization, GPT, BERT, Entity Recognition, AI technologies, Stemming, SpaCy, Text Summarization, Generative AI
Skills:
causal inference , Databricks, Clustering, Time Series Analysis, Azure Synapse Analytics, Azure Machine Learning, Recommender Systems, Hypothesis Testing, uplift modeling, statistical methods, Azure Data Lake Storage, Regression, Classification, dashboard development, lifetime value modeling, personalization algorithms, experimentation design
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