Master Thesis Projects in AI Tooling & Infrastructure
Zenseact.com
Office
Lund, Sweden
Full Time
🧠 Build The Ai Backbone Behind Safer Autonomous Driving
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.
Let’s take a closer look at what this cluster is all about:
Behind every intelligent decision an autonomous vehicle makes is a powerful ecosystem of data, tools, and infrastructure. In this master thesis cluster, you’ll design the platforms and frameworks that enable large-scale AI development — from data pipelines and simulation to distributed learning and knowledge transfer.
Your work is more
than engineering — it enables everything else. The systems you create will help
perception, planning, and decision-making models train faster, scale smarter,
and continuously improve, forming the foundation of safer autonomous driving.
🔬 Ai Tooling & Infrastructure: Thesis Projects (Cluster B)
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?
Passionate and 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
Because this cluster spans multiple topics, requirements vary. In your application, please list all relevant skills/tools and your experience level for each (basic / intermediate / advanced). This helps us match you with the best project.
Typical skills 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?
Submit your CV, motivation letter, and grade transcripts.
Applying as a pair? Please include your partner’s name in the application.
- Planned start: January 2026 (flexible)
- Application deadline: October 31, 2025 (applications reviewed continuously)
- For questions, contact: Gabriel Campos, Research Manager – gabriel.campos@zenseact.com
This
role may involve access to sensitive information, trade secrets, and
confidential data. Selected candidates may undergo a background check as part
of the recruitment process.
More About Zenseact
🚗 Our software makes a difference
We use AI-driven technology to fight traffic accidents and make roads safer. Every year, 1.4 million people lose their lives in traffic — we’re here to change that.
🎯 One purpose, one product
We design the complete software stack for autonomous driving and advanced driver-assistance systems. With continuous updates, cars become safer over time — bringing us closer Towards Zero. Faster.
❤️ Culture with people at heart
We can only succeed
together. Our culture is built on care, trust, and belonging — a place where
everyone 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.
Master Thesis Projects in AI Tooling & Infrastructure
Office
Lund, Sweden
Full Time
October 3, 2025