2023-08-23 14:48:55

Data Scientist for LLM Applications f/m/d

CVKeskus.ee klient
5000 €/m Gross

Job Description

Data scientists at AVL are responsible to develop and execute software algorithms, including the integration and fine-tuning of pre-trained models (such as cutting-edge LLMs), to extract information from structured and unstructured data in cooperation with domain experts of the according technical field. You have a strong experience using a variety of data analytics methods and tools, developing and implementing models and algorithms. You have proven ability to drive business results with their data-based insights and are comfortable working with a wide range of stakeholders and functional teams. You have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.


  • Work with stakeholders throughout the organization to identify opportunities using data and knowledge from the automotive domain to drive business solutions
  • Design and implement metrics, applications and tools that will enable engineers to derive better conclusions (ad-hoc and automated analysis cases)
  • Apply statistical modeling, learning and machine learning techniques to optimize processes and support engineering decisions
  • Organize an interdisciplinary LLM exchange group, applying models to analyze automotive data, design concepts and metrics to optimize engineering processes 
  • Design graphical representations and visuals that engineers can easily interpret and understand
  • Support the scale out of design algorithms via implementation in larger software frameworks
  • Active support and engagement for pre-sales and sales activities


  • Advanced degree (MSc, MEng, or PhD) in a relevant field such as Statistics, Mathematics, Computer Science, or a related Engineering discipline
  • Strong proficiency in Python and experience in scalable processing environments like Spark or Dask preferable
  • Proven experience in applying data science methods in industrial use cases
  • Strong soft skills in leadership, communication, and facilitation within teams and diverse stakeholder environments with conflicting requirements
  • Strong problem-solving skills for clarifying and resolving ambiguous problem statements with available data
  • Experience building and deploying machine learning models in a professional environment.
  • Experience with open source LLMs, as well as with public APIs and open source libraries for working with LLMs
  • Understanding knowledge graphs, vector databases, document embedding, and text search
  • Experience with prompt engineering and retrieval augmented generation, as well as with classical natural language processing techniques and tools
  • Highly developed quality awareness with strong attention to details, ability to work in team, organizational skills
  • Willingness to travel in the context of project execution
  • German skills preferred, fluent in English

Company offers

  • Home office
  • Flexitime Regulation
  • Canteen
  • Award-winning Training Programs
  • Health Management
  • Parental Leave Management (Maternity/Paternity Protection & Educational Leave)


Annual Remuneration: Due to the Austrian Equal Treatment Act we are obligated to state the annual gross remuneration (full-time) for this position as a basis for negotiation: €60,000.00. The Employee will be classified according to the Collective Agreement for Employees of Industry (Collective Bargaining Agreement of the Automotive Industry). We will, in any case, offer market-conforming payment taking qualifications and professional experience into account.



If so, please use our online application tool to send your application to AVL!


At AVL, we foster and celebrate diversity: We recognize that diverse ways of thinking are required to achieve our vision of a greener, safer, and better world of mobility. Different backgrounds, attitudes, interests, and experiences make us successful. As Equal Opportunity Employer we consider all qualified applicants without regard to ethnicity, religion, gender, sexual orientation or disability status.