Master Thesis Projects in AI Tooling

This year, we're trying something a little different to make it easier for you to explore and apply for our master thesis projects. Instead of separate ads for every topic, we've grouped all projects into three main clusters — each focused on a different part of autonomous driving. You're welcome to apply to one, two, or all three clusters if you like, but later in the application process, we'll ask you to prioritize the projects you're most excited about, in each cluster.

Build the AI Backbone Behind Safer Autonomous Driving

Behindevery intelligent decision an autonomous vehicle makes is a powerful ecosystemof data, tools, andinfrastructure. In this master thesis cluster, you'lldesign the platforms and frameworks that enable large-scale AI development —from data pipelines and simulation to distributed learning and knowledgetransfer.

Your work is morethan engineering — it enables everything else. The systems you create will helpperception, planning, and decision-making models train faster, scale smarter,and continuously improve, forming the foundation of safer autonomous driving.

AI Tooling & Infrastructure: Thesis Projects (ClusterB)

Here are the master thesis projects offered in this cluster — each topic below is a separate project you can apply for:

• Project 1:  Compression of LiDAR point clouds for visualization – Develop efficient compression to make large sensor datasets easier to visualize, store, and process.
  
• Project 2:  Scalable Data Engine for Perception Tasks in Autonomous Driving – Build high-performance data pipelines for large-scale training and evaluation.
  
• Project 3:  Generation of naturalistic synthetic eyes – Create realistic synthetic perception data to support safer, more robust model training.
  
• Project 4:  Scalable Federated Learning for Autonomous Driving with Self-Supervision – Enable distributed training across fleets while preserving privacy and improving scalability.
  
• Project 5:  Communication-Efficient Federated Learning for Autonomous Vehicles – Design solutions that minimize communication overhead while maintaining model performance.
  
• Project 6:  Efficient Knowledge Transfer in Heterogeneous Autonomous Driving Systems – Explore strategies to share learned knowledge between different vehicle platforms and models.
  
  

Depending on which project you're offered, you'll get to work on designing and implementing AI infrastructure components that power large-scale development. You'll handle real-world data, contribute to scalable training pipelines, and explore advanced techniques such as federated learning, simulation, and knowledge transfer. Throughout the projects, you'll collaborate closely with experienced researchers and engineers — and the results of your work will directly contribute to accelerating the development of safer, smarter autonomous vehicles.

We offer several master thesis projects across three clusters:

• Sensing & Perception – how the car sees and understands the world
• AI Tooling & Infrastructure (this one) – the data, platforms, and tools that power autonomous systems
• Planning, Decision-Making & Safety – how the car predicts, plans, and acts intelligently

Each cluster has its own job ad and a detailed project PDF with background on all topics. You'll receive the PDF in a separate email after you apply to help you explore projects in depth.

 So Who Are We Looking For?

Passionateand curious Master's students from (including but not limited to):

• Computer Science / Software Engineering
• Machine Learning / Artificial Intelligence
• Data Science / Big Data
• Distributed Systems / Cloud Computing
• Embedded Systems / Autonomous Systems

 Expected Skills & Experience

Becausethis cluster spans multiple topics, requirements vary. In your application,please list all relevantskills/tools and your experience level for each (basic /intermediate / advanced). This helps us match you with the best project.

Typicalskills we look for (you do not need all of these):

• Programming in Python, C++ and/or Cloud
• Familiarity with ML or data-engineering pipelines
• Experience with deep learning frameworks (PyTorch, TensorFlow)
• Knowledge of distributed systems, federated learning, or simulation environments
• Interest in scalability, data infrastructure, or MLOps
  
  

What's in It for You?

• Contribute to the core infrastructure that powers autonomous driving
• Hands-on experience with real-world data, scalable AI systems, and advanced tools
• Collaboration with industry experts on impactful, production-oriented solutions
• Join a diverse, inclusive team shaping the future of mobility
  
  

How to Apply?

Submityour CV, motivation letter, andgrade transcripts.

Applying as a pair?Please include your partner's name in the application.

• Planned start: January flexible)
• Application deadline: October 31, 2025 (applications reviewed continuously)
• For questions, contact: Gabriel Campos, Research Manager –

Thisrole may involve access to sensitive information, trade secrets, andconfidential data. Selected candidates may undergo a background check as partof the recruitment process.

More about Zenseact

Our software makes a difference

Weuse AI-driven technology to fight traffic accidents and make roads safer. Everyyear, 1.4 million people lose their lives in traffic — we're here to changethat. 

One purpose, one product

We design thecomplete software stack for autonomous driving and advanced driver-assistancesystems. With continuous updates, cars become safer over time — bringing uscloser Towards Zero. Faster.

Culture with people at heart

We can only succeedtogether. Our culture is built on care, trust, and belonging — a place whereeveryone can grow, be themselves, and do their best, at work and in life.

Zenseact works proactively to create a culture of diversity and inclusion, where individual differences are appreciated and respected. To drive innovation we see diversity as an asset, which means we value and respect differences in gender, race, ethnicity, religion or other belief, disability, sexual orientation or age etc.

Interviews are held on a continuous basis, so we highly recommend that you submit your application at your earliest convenience.

---