We have built a digital sales assistant SaaS application that contains a lot of sales pitch data matched with differing categorical data types. Our goal is to match this unstructured data with structured public company and contact data. We would like to be able to recommend what to say if you are calling a decision-maker in a specific industry, based on what we can see works. Right now we are using OpenAI Chat completions API to generate pitch content based on our own templates and website text, but we would like to have more control over the output quality and variation.
- Building a NLP pipeline for;
- Data collection and cleaning from self-developed SaaS applications
- Annotating and curating sales pitch data using an annotation tool (like Argilla or Prodigy)
- Fine-tuning large language models with the annotated sales pitch data
- Deployment and monitoring of model performance and updating model(s)
- In-app curation of pitch data
- Experience with some or all of the below
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Interviews are held on an ongoing basis with a start date as soon as possible. If you have any questions please feel free to reach out to our COO, Niclas Meyer by email or by phone. For more information or questions please contact us at firstname.lastname@example.org or phone number +45 26 13 27 31. We look forward to hearing from you!
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