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Data & AI Engineer Automotive

GlobalLogic Sweden AB · Göteborg

posted 3d ago, verified live

Key factors at a glance

Seniority
Junior
Experience
0+ years
Work mode
Salary
Not stated
Required working language
English

Must-haves

  • Master's degree in Data Science or Artificial Intelligence
  • Python programming
  • Pandas, NumPy, Matplotlib
  • Machine learning fundamentals (time-series, classification, clustering, anomaly detection)
  • Generative AI and LLM fundamentals

Nice-to-haves

  • Computer Vision and OpenCV
  • Image Classification and Object Detection
  • TensorFlow or PyTorch
  • Tableau
  • Git/version control
  • NLP exposure
PythonpandasPyTorchTensorFlowLLMs

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Original posting

English

GlobalLogic is looking for a Data & AI Engineer to join an innovative team working at the intersection of Artificial Intelligence, data analytics, and automotive software verification. The team is developing an AI-based Measurement Analytics Tool designed to unlock insights from the large volumes of measurement data generated during vehicle software testing. The solution will help engineering teams reconstruct tests from measurement data, identify usage patterns, detect abnormal behaviour, analyse faults, and generate test and fault reports more efficiently. This is an excellent opportunity for a recent graduate or early-career engineer who has strong Python fundamentals, an interest in AI/ML, and a passion for solving real-world engineering problems. You will work alongside experienced software and test engineers and automotive domain experts, gaining hands-on exposure to vehicle systems, measurement data, diagnostic logs and modern AI technologies. Job Responsibilities AI/ML Development Support: Assist with the development, testing, and documentation of AI/ML components and data-processing pipelines for automotive measurement data. Data Cleaning & Analysis: Parse, clean, structure, and analyse numerical telemetry, vehicle signals, diagnostic logs, and other measurement data. Test Data Analytics: Support the identification of predefined test patterns within vehicle measurement data and generate test results and coverage analysis. Machine Learning & Prototyping: Implement and evaluate basic analytical models, including time-series analysis, classification, clustering, and anomaly detection. AI/LLM Support: Assist with developing and testing AI/LLM-based assistants, including prompt engineering and evaluation of AI-generated responses for test analysis. User Journey Analysis: Analyse historical vehicle usage data to identify patterns and support the generation of representative/synthetic user journeys. Python Development: Write clean, maintainable, and well-documented Python code for data processing, analytics, and automation. API & UI Development: Assist in developing simple APIs and web-based interfaces to expose data analytics and AI capabilities. Technical Collaboration: Work closely with senior engineers and automotive domain experts to understand requirements, learn vehicle systems, and implement solutions under guidance. Documentation: Document technical solutions, analysis results, experiments, and developed components. Requirements: Master’s degree in Data Science or Artificial Intelligence Solid foundational programming skills in Python. Ability to write Python scripts to parse, filter, transform, and analyse raw data such as CSV files, text files, logs, and telemetry data. Familiarity with Python data-analysis libraries such as Pandas, NumPy, and Matplotlib. Understanding of data structures, algorithms, and software development principles. Proficient in Computer Vision, OpenCV, Image Classification, Object Detection, TensorFlow, PyTorch and Tableau Exposure to machine learning fundamentals, such as time-series analysis, classification, clustering, anomaly detection, or introductory NLP. Skilled in Generative AI, LLMs, and prompt engineering. Familiarity with Git/version control is an advantage. Strong analytical and problem-solving skills. High curiosity and willingness to learn new technologies and complex technical domains. Good communication and collaboration skills, with the ability to work effectively with senior engineers and domain experts.

Shown in its original English. To apply, continue to the company's own page.