Software Engineer, Applied AI Integration Internship

1 Month ago • Upto 1 Years • Artificial Intelligence • Research & Development

Job Summary

Job Description

Tesla's Service Engineering team seeks a talented Software Engineering intern to leverage AI/ML for improving infotainment diagnostics. The internship involves working with large datasets to identify key issues, utilize LLMs and data analysis to categorize customer requests, and build ML models to reduce infotainment diagnostic time. Responsibilities include data analysis using Pandas, NumPy, or PySpark; building and training ML models with Scikit-learn, TensorFlow, or PyTorch; and interfacing with LLM APIs. The internship is a full-time, 6-month position in Amsterdam starting March 2025. Successful candidates will possess strong AI/ML foundations and familiarity with relevant tools and languages.
Must have:
  • Familiar with ML model building (Scikit-learn, TensorFlow, PyTorch)
  • Experience with data analysis (Pandas, NumPy, PySpark)
  • LLM API interaction experience
  • Proficient in Python, C/C++
  • C1 English level
Good to have:
  • Experience with SQL/NoSQL databases
  • Familiarity with Linux/Unix systems

Job Details

What to Expect

Start date: March 2025
Location: Amsterdam
Duration: 6 months
Fulltime position (40 hours a week)

NOTE: YOU MUST BE ENROLLED IN EDUCATION DURING THE ENTIRE INTERNSHIP TO BE CONSIDERED.

Within Tesla Vehicle Software organization, the Service Engineering team serves as a link between service, development, and manufacturing teams worldwide for all vehicle sub-systems. We review and investigate field issues by analyzing logs and source code, work with relevant software engineers or component owners to implement solutions and improve our products. We also develop software tools to ensure that customer vehicles are diagnosed and repaired accurately, reliably, and as efficiently as possible.

We are seeking a talented engineering intern with a strong foundation in AI/ML to explore opportunities for improving diagnostics of infotainment issues (e.g., Bluetooth, Wi-Fi, Audio, Display) based on vehicle/service data and customer service requests.

What You’ll Do
  • Work with vast sources of Service-related data to infer top impacting issues
  • Leverage Large Language Models (LLMs) and data analysis to better understand and categorize customer service requests
  • Utilize fleet-wide data to prototype ML models that reduce the time needed to diagnose and root cause new infotainment issues
What You’ll Bring
  • Currently enrolled in programs related to Machine Learning / Computer Science
  • Familiar with building and training machine learning models using tools like Scikit-learn, TensorFlow, or PyTorch – and scripting workflows to interface with LLM APIs
  • Understanding of model evaluation metrics
  • Experience with data analysis and libraries like Pandas, NumPy, or PySpark and databases (SQL/NoSQL)
  • Familiar with Linux / Unix Systems
  • Familiar with Python, C/C++
  • Level C1 in English (spoken and written)

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