Start date: asap
Planned duration: 12 months
Extension: possible
Your tasks:
Solve core ML and data engineering challenges, handling model deployment and relevant backend/frontend engineering; as well as model evaluation, and finetuning.
Develop methods for semantic interpretation and automated redundancy removal of proprietary documents.
Devise experiments to help our understanding of a good knowledge base for LLM Agents.
Build pipelines that span data collection, document preparation and pre-processing, RAG implementation and LLM evaluation for different internal applications and use cases
Benchmark and evaluate optimization techniques to ensure efficiency and performance.
Familiarize yourself with diverse document sources and formats.
Measure and analyze the pipeline's performance, providing data-driven insights for improvement.
Work closely with cross-functional teams, communicating results clearly to key stakeholders across RDI Operations to ensure the product's reliability and project success.
Your Profile:
MS/PhD in Computer Science, Data Science, Statistics, (Computational) Linguistics or related fields
Experience in machine learning or related fields
Demonstrated technical capabilities in deploying and evaluating machine learning models in production environments or in ML/LLM research
Strong programming skills in Python and deep learning frameworks such as PyTorch, Tensorflow, JAX
A dynamic and resilient individual who is open to work in an evolving project environment, taking initiative to shape the project, continuously learning and adapting to new challenges and opportunities
Good communication skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiences
Fluent in German and English
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