Machine Learning Engineer
Machine Learning Engineer
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Job Description
The role will sit in the Digital Technology (DT) Regulatory Stakeholders department and will be part of the team reporting to the DT Lead AI for Clinical Development. The team focuses on building (Gen)AI solutions for the Clinical Development stakeholders.
The use cases we are working on rely on GenAI to make writing documents or finding relevant information easier thus helping bring drugs to patients faster and more efficiently. The DT ML Engineer Clinical Development will be responsible for developing and implementing machine learning models and AI solutions to support clinical development projects. The role involves working closely with stakeholders to understand their needs analyzing and improving data pipelines and ensuring the quality and efficiency of AIdriven processes. The engineer will also be tasked with researching and integrating new AI technologies to enhance the clinical development workflow.
Key Responsibilities:
Develop GenAI assistants to support clinical development.
Build data pipelines to parse documents using custom developed and offtheshelf methods (document intelligence entity recognition ...).
Collaborate with stakeholders to understand their requirements and present datadriven insights.
Research and evaluate different AI models and technologies for potential integration.
Develop backend framework using Python and FastAPI.
Ensure the quality and efficiency of AI solutions through continuous testing and optimization.
Requirements
Qualifications:
Experience with ML/AIbased products particularly generative AI (LLM embedding)
Experience in the healthcare pharmaceutical or clinical development sector is a plus.
Proficiency in Git Python Experience with FastAPI is a plus.
Strong knowledge of ML/(gen)AI frameworks and libraries specifically Langchain and
transformers.
Experience with data analysis and visualization tools such as Pandas and NumPy.
Experience working with cloud platforms such as AWS or Azure specifically Azure AI. Familiarity with Kubernetes is a plus.
Required Soft Skills:
Entrepreneurial spirit with a handson mentality.
Strong learning attitude and independence.
Motivated enthusiasm and ambition.
Critical thinking with an open investigative attitude.
Sense of responsibility and initiative with a commitment to delivering highquality work.
Benefits
Employment Type
Full Time
