Machine Learning DevOps Engineer for Automated Driving, Cluj
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At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people's lives. Whether in areas of Automated Driving, Electric & Connected Mobility, IoT or Connectivity, our ideas make driving safer and more comfortable than ever before. This is only possible with the help of more than 1000 talented engineers from Bosch Engineering Center Cluj specialized in software, hardware & mechanics and reliability engineering, who work closely together with other Engineering Centers within Bosch and with Bosch Cluj Plant in order to offer unique products and AIoT solutions to our clients from around the world.
So, are you ready to shape the future of the mobility together with us? Let us tell you more. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference.Qualifications
- You have at least 2-3 years of experience in Cloud Infrastructure or DevOps roles
- You have experience with version control systems such as Git
- Comfortable working with both structured and unstructured data (SQL, NOSQL)
- You have good knowledge of Linux operating systems;
- You have strong expertise with public cloud platform (Azure is a plus) and agile methodologies;
- You have hands on experience with IaaC.
- You have hands on experience and good understand of Jenkins, Docker, Kubernetes and cloud based solutions.
- You have experience in implementing CI/CD Pipelines and hands on experience with Azure DevOps or Jenkins;
- You have very good understanding of Continuous Delivery and DevOps ways of working;
- You have proven experience in operations for Java, Python cloud based solutions.
We would also appreciate :
- If you are willing to travel;
- If you have public Cloud / Kubernetes Certification(s);
- If you have relevant experience in working in high-performant agile software teams with a DevOps mindset.
You would be a perfect match to our team if:
- You are a very good communicator, capable to connect the various stakeholders;
- You have excellent at prioritization, time management, excellent follow-through skills;
- You are a strong team player;
- You show passion for new technologies and innovation;
- You have C++ knowledge as well
The languages you should know:
- English - a good level is mandatory
- German - it is not mandatory, but it is an advantage
Ways of Working
Hybrid working is the new way of working! We offer super nice and cozy office spaces, however you can also work from home if you feel like it (70% remote work)
Our #LikeABosch benefits:
- 25 days of annual leave
- Medical subscription
- Accident insurance
- A monthly budget which can be used for several different services on an online benefit platform
- Annual bonus
- Relocation bonus
- Lunch discounts
- Sport activities and well-being initiatives
- Technical and soft skills trainings
- Access to e-learning platforms
- Local and Global career development programs
- Bookster subscription
We are currently looking for a "Machine Learning DevOps Engineer for Automated Driving" to work within our team.
You will be part of the team that develops technology solutions for Big Data Management in driver assistance and autonomous driving (extracting data from sensors), creating internal tools, cloud functionalities for car fleet management and improving the algorithms on sensors.
You will cover topics of data engineering for automated driving, connected validation for automated driving and synthetic video scenes.
In your role you will:
- Plan and implement a stable, highly available, high-performance and secure infrastructure - using a multiservices architecture
- Monitor and troubleshoot anomalies
- Take care so that the automation systems are up to date.
- Work close with architects and data analysts and create scripts and tools for process automation.
- Building and monitoring models, data and services (eg.: ML inferences)
- Track and manage machine learning experiments
- Test code, validate data integrity, model quality
- Leave a mark by giving training and coaching others
- Assuring communication between services using cloud networking
- Operating ETL(Extract Transform Load) pipelines
- Asses and choose cloud specific services for ML