Expleo Group ir globāls inženierzinātņu, tehnoloģiju un konsultāciju partneris, kas palīdz organizācijām pārveidot darbību, izstrādāt sarežģītus produktus un uzlabot ražošanas un kvalitātes procesus. Uzņēmuma darbība aptver konsultācijas, aizsardzības nozari un loģistiku, bet tā kompetences ietver mākslīgo intelektu, digitalizāciju un kiberdrošību. Expleo, kas dibināts 1966. gadā, apvieno vairāk nekā piecu gadu desmitu pieredzi ar 18 000 ekspertu komandu, kas strādā 29 valstīs, lai atbalstītu inovācijas un darbības rezultātus.
QDM Engineer, AI and Machine Learning
Build Python and machine learning solutions using automotive plant data and connected data pipelines. Help Expleo advance safer, smarter, and more sustainable mobility.
Apraksts
- Develop technology for autonomous vehicles, electric mobility, and digitalisation.
- Help automotive clients improve performance and sustainability through ongoing innovation.
- Integrate technologies that enhance vehicle safety, efficiency, and environmental impact.
- Contribute to safer, smarter, and greener transport.
- Set up systems to collect, store, process, and visualize plant data.
- Bring machines, PLCs, sensors, MES, ERP, quality systems, and manual data sources together on a shared platform.
- Build data pipelines for automated transfer and integration.
- Protect data through security, backup, and access controls.
- Explain complex technical ideas to non-technical stakeholders.
Prasības
- Bring 2–5 years of practical experience in data analysis and machine learning; diploma holders need 3–6 years.
- Use Python and relevant libraries such as pandas, scikit-learn, TensorFlow, and PyTorch.
- Understand statistical analysis and machine learning algorithms.
- Have experience with Matplotlib, Seaborn, and Tableau for data visualization.
- Be familiar with SQL and database management.
- Understand data infrastructure, including data collection, storage, processing, and visualization.
- Have experience connecting machines, PLCs, sensors, MES, ERP, quality systems, and manual data sources to a shared platform.
- Have experience building data pipelines for automated data transfer and integration.
- Understand data security, backups, and access control.
- Apply strong problem-solving skills and attention to detail.
- Work effectively both independently and as part of a team.
- Communicate complex technical ideas clearly to non-technical stakeholders.
- Handle basic operations in Excel, PowerPoint, and Word.
- Hold a BE in Mechanical or Automobile Engineering, Computer Science, Data Science, Statistics, or an equivalent field; alternatively, a DME in Mechanical or Automobile Engineering or equivalent.
- Show willingness to learn and deploy solutions.
- Communicate effectively with different stakeholders.
- benefits and fields.
Priekšrocības
- Work in a collaborative environment.
- Access ongoing learning and accredited training courses.
- Use a world-class learning ecosystem.
- Work with leading companies and brands across a range of sectors.