Verification Engineering Trainee (f/m/div)

Infineon Technologies
Bristol
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist (Mid level)

Data Scientist

Data Scientist- Fintech

Data Scientist

Senior Manager, Data Science - eBay Live

Does your creative and analytical thinking make you the go-to person to solve problems? Are you a technology enthusiast, eager to develop your skills and face new challenges? Then you might be the team player we are missing! Apply now and join our dynamic environment in Bristol.As a Verification Engineering Trainee, you will be working within the Compute and ADAS IP Development teams in Bristol. You will take a responsible role in the verification of cutting-edge real time compute and ADAS radar processing designs for the future of driving including electric and autonomous cars.

In your new role, you will:

• Understand the process ofdeveloping IPs for the AURIX familyand the complex product specifications;
• Collaborate witharchitecture and design teams;
• Use SystemVerilog UVM tocreate the verification environmentanddebug test fails;
• Learn how todetermine when verification is complete;
• Use a range of software tools toincrease efficiency and produce accurate results;
• Have the potential towork with innovative methods, such as Machine learning,to improve our workflows;
• Work within Infineonquality and functional safety process frameworks;
• Contribute across the team tosolve challenges in achieving on-schedule deliveriesof high-quality subsystems.You have a result-oriented and proactive mindset and are a team player with good interpersonal skills. Furthermore, you are eager to learn about new, cutting-edge technology and have creative and analytical skills that support you in solving problems as well as ensuring a successful outcome.

You are best equipped for this job if you:

• Have adegree in Engineering, Science, TechnologyorMaths;
• Understand theprinciples of scripting( in Python);
• Have goodtime management skills;
• Fluency in English.
It will be an advantage if you also have:
• Capability to useEDA software tools;
• Some experience inadvanced verification languages(SystemVerilog, Specman-e, SystemC).

This paid internship is a first step into a successful career with us! Please send us yourCV in Englishso we can get to know you better.

Benefits

Coaching, mentoring networking possibilities Wide range of training offers & planning of career development Different career paths: Project Management, Technical Ladder, Management & Individual Contributor Flexible working conditions Part-time work possible (also during parental leave) Sabbatical Medical coverage Labor gymnastics Private insurance offers Wage payment in case of sick leave Corporate pension benefits IFX Success Bonus and Spot Awards Accessibility, access for wheelchairs

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.