As a Bosch intern you will benefit from on-the-job training in a supportive working environment where you can develop your personal and professional skills. As an AI & Machine Learning Engineering intern within the Powertrain domain your day-to-day tasks will vary but could include the following:
- Contribute to developing real-world AI/ML models for cutting-edge powertrain applications including predictive maintenance anomaly detection and performance optimisationdirectly influencing the next generation of automotive technology.
- Work hands-on with high-value powertrain datasets supporting the preparation cleaning and analysis of data from vehicle test benches in-vehicle logs and advanced simulation environments.
- Help build intelligent data processing and automation tools that enhance engineering workflows and accelerate innovation across Boschs powertrain engineering teams.
- Participate in the full lifecycle of ML development including algorithm design model training testing validation and performance evaluation while learning industry-standard AI practices.
- Collaborate closely with experienced Bosch engineers and customer teams contributing to data analysis debugging AI-driven tools and supporting technical investigations that have real customer impact.
- Support the integration of AI and ML solutions into live testing and calibration environments such as Hardware-in-the-Loop (HiL) systems and simulation frameworks gaining exposure to state-of-the-art automotive engineering platforms.
As well as good technical competency you will be expected to be highly organised and able to juggle multiple tasks and demands by anticipating the needs of others and looking for proactive solutions so you will have the following attributes:
- Results orientated; with a desire to exceed targets.
- Proactive and self-motivated.
- Builds high-quality and lasting relationships with all stakeholders; makes people feel appreciated even in difficult situations.
- Deals constructively with conflict; resilient.
- Uses analytical skills in order to solve complex tasks and takes sound decisions.
- Good interpersonal/communication skills.
Qualifications :
Essential:
- Studying for a relevant undergraduate degree and required to take a placement as part of your course (Engineering Computer Science Data Science or similar preferred).
- Strong interest in AI Machine Learning and data-driven engineering ideally with some exposure through modules or projects.
- Understanding & Interest in core ML concepts such as data processing regression/classification model validation or neural networks.
- Ability to organise own work and work autonomously.
- Good analytical skills and interpersonal communication and collaboration skills.
- Good written and spoken English.
- Proficient in MS office.
- Full UK driving license is required.
Desirable:
- Basic proficiency in Python desirable; familiarity with Matlab/Simulink or C is an advantage.
Additional Information :
This is a 12-month internship beginning in Summer 2026. This position is open to undergraduate students who are required to partake in a work placement as part of their course.
Location: you will be based at the Coventry office.
Shortlisted candidates will then be invited to participate in a face-to-face interview by the hiring team and/or an online assessment centre.
You must have the right to live and work in the UK when you start your placement and for the full duration of your placement. Please note your placement must be directly relevant to your course to comply with visa requirements.
Before attending an interview for this position you must inform your Faculty/School Placement Officer and we strongly suggest you check you are eligible for a placement before you apply. If your Faculty/School does not have a Placement Officer you must inform your course tutor.
Deadline for applications: 2nd January 2026
Remote Work :
No
Employment Type :
Full-time
As a Bosch intern you will benefit from on-the-job training in a supportive working environment where you can develop your personal and professional skills. As an AI & Machine Learning Engineering intern within the Powertrain domain your day-to-day tasks will vary but could include the following: Co...
As a Bosch intern you will benefit from on-the-job training in a supportive working environment where you can develop your personal and professional skills. As an AI & Machine Learning Engineering intern within the Powertrain domain your day-to-day tasks will vary but could include the following:
- Contribute to developing real-world AI/ML models for cutting-edge powertrain applications including predictive maintenance anomaly detection and performance optimisationdirectly influencing the next generation of automotive technology.
- Work hands-on with high-value powertrain datasets supporting the preparation cleaning and analysis of data from vehicle test benches in-vehicle logs and advanced simulation environments.
- Help build intelligent data processing and automation tools that enhance engineering workflows and accelerate innovation across Boschs powertrain engineering teams.
- Participate in the full lifecycle of ML development including algorithm design model training testing validation and performance evaluation while learning industry-standard AI practices.
- Collaborate closely with experienced Bosch engineers and customer teams contributing to data analysis debugging AI-driven tools and supporting technical investigations that have real customer impact.
- Support the integration of AI and ML solutions into live testing and calibration environments such as Hardware-in-the-Loop (HiL) systems and simulation frameworks gaining exposure to state-of-the-art automotive engineering platforms.
As well as good technical competency you will be expected to be highly organised and able to juggle multiple tasks and demands by anticipating the needs of others and looking for proactive solutions so you will have the following attributes:
- Results orientated; with a desire to exceed targets.
- Proactive and self-motivated.
- Builds high-quality and lasting relationships with all stakeholders; makes people feel appreciated even in difficult situations.
- Deals constructively with conflict; resilient.
- Uses analytical skills in order to solve complex tasks and takes sound decisions.
- Good interpersonal/communication skills.
Qualifications :
Essential:
- Studying for a relevant undergraduate degree and required to take a placement as part of your course (Engineering Computer Science Data Science or similar preferred).
- Strong interest in AI Machine Learning and data-driven engineering ideally with some exposure through modules or projects.
- Understanding & Interest in core ML concepts such as data processing regression/classification model validation or neural networks.
- Ability to organise own work and work autonomously.
- Good analytical skills and interpersonal communication and collaboration skills.
- Good written and spoken English.
- Proficient in MS office.
- Full UK driving license is required.
Desirable:
- Basic proficiency in Python desirable; familiarity with Matlab/Simulink or C is an advantage.
Additional Information :
This is a 12-month internship beginning in Summer 2026. This position is open to undergraduate students who are required to partake in a work placement as part of their course.
Location: you will be based at the Coventry office.
Shortlisted candidates will then be invited to participate in a face-to-face interview by the hiring team and/or an online assessment centre.
You must have the right to live and work in the UK when you start your placement and for the full duration of your placement. Please note your placement must be directly relevant to your course to comply with visa requirements.
Before attending an interview for this position you must inform your Faculty/School Placement Officer and we strongly suggest you check you are eligible for a placement before you apply. If your Faculty/School does not have a Placement Officer you must inform your course tutor.
Deadline for applications: 2nd January 2026
Remote Work :
No
Employment Type :
Full-time
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