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ZF is a global technology company supplying systems for passenger cars, commercial vehicles and industrial technology, enabling the next generation of mobility.

ZF allows vehicles to see, think and act. In the four technology domains of Vehicle Motion Control, Integrated Safety, Automated Driving, and Electric Mobility, ZF offers comprehensive product and software solutions for established vehicle manufacturers and newly emerging transport and mobility service providers. ZF electrifies a wide range of vehicle types. With its products, the company contributes to reducing emissions, protecting the climate and enhancing safe mobility.

Machine Learning Engineer (m/f/d)

Country/Region:  ES
Location: 

Barcelona, ES, 08018 Barberá del Vallés, ES, 08210

Req ID 44867 Barcelona, Barberá del Vallés, Spain
     

We are looking for a new colleague in the Global Commercial Excellence department of ZF Aftermarket at our location in Barcelona or District 22@ Barcelona.

 
ZF is growing its advanced analytics competencies, and will open a brand new location near 22@Barcelona “Districte de la innovació” to rocket thrust data innovation forward in an environment ideal for technological breakthroughs, passion for the sciences, entrepreneurial mindsets, and excellent work-life balance. The aftermarket environment is undergoing a massive shift in electrified, connected, intelligent and shared mobility, and we invite you to watch the following keynote speech from our Vice President outlining ZF’s exciting new strategy in this space:

https://youtu.be/fDoYd9ZP8Nk?t=175.


Your tasks:

  • While the data scientists spend time understanding the business, prototyping algorithms, being in charge of the statistical aspects of the model, the Machine Learning Engineer takes the prototype requirements and optimizes the implementation
  • Ensure that Machine Learning models are implemented in the most efficient manner, so that the application can run smoothly and be easily understood in case of handover/bugs
  • Improve the efficiency of the data scientists by building reusable pieces of code to make data science work more efficient
  • Define coding standards and ensure that the team are adopting them 
  • Partner with IT to define Machine Learning model monitoring
     

Your  profile:

  • Degree in computer science with emphasis in machine learning or equivalent in experience
  • Strong Experience in Python, R and Spark (Pyspark is desirable)
  • Deployment of Machine Learning models in production including industry experience in agile development and DevOps (Docker, Kubernetes)
  • Working experience with Databases (ex. Oracle, AWS S3) and Big Data platforms (ex. Databricks, GCP, Cloudera)
  • Team player, business acumen, fluent English

 

The position is part of the ZF Global Employee Referral Program.

 

About ZF:
ZF is a global technology company suppling systems for passenger cars, commercial vehicles and industrial technology, enabling the next generation of mobility. ZF allows vehicles to see, think and act. In the four technology domains of Vehicle Motion Control, Integrated Safety, Automated Driving, and Electric Mobility, ZF offers comprehensive product and software solutions for established vehicle manufacturers and newly emerging transport and mobility service providers. ZF electrifies a wide range of vehicle types. With its products, the company contributes to reducing emissions, protecting the climate and enhancing safe mobility. In fiscal year 2020 ZF reported sales of €32.6 billion. 
The company employs more than 150,000 associates at approximately 270 locations in 42 countries.

 

Be part of our ZF team as Machine Learning Engineer (m/f/d) and apply now!

Contact

Elise Cosquer

+49 211 584 222 221

Our Commitment to Diversity

ZF is an Equal Opportunity and Affirmative Action Employer and is committed to ensuring equal employment opportunities for all job applicants and employees. Employment decisions are based upon job-related reasons regardless of an applicant's race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, marital status, genetic information, protected veteran status, or any other status protected by law.

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