How would it feel to work at the cutting edge of Deep Learning together with other highly skilled engineers and researchers with brilliant minds, from all over the world – and get access to one of the largest GPU clusters in Sweden? And how would you feel to see your breakfast idea come to life in a real car that very same day? How about doing this in a really warm, inclusive culture, that values innovation, trust and collaboration and truly has people at heart? Apply today - with or without CV, all we need is contact info at first stage. We'll cover the rest later. 

Insights from the team

The Deep Learning teams at Zenseact are at the core of everything Zenseact is. We have the arguably hardest Deep Learning use case out there – self driving cars. With the purpose of going Towards zero. Faster – meaning zero traffic accidents. Working with deep learning at Zenseact means working where the magic happens, at the forefront of what technology can do, to support and drive safety! We are investing heavily in our Deep Learning platform, both in terms of people and hardware. We've been ramping up significantly for a while, going towards the largest GPU cluster in Sweden and we’ve built several new teams in DL. We work on applying deep learning to the perception task in the broad sense. Both in single sensor single frame setups with late fusion, as well as early sensor fusion with temporal processing and output on the planning level, in an end-to-end fashion. To support this, we build state of the art tools for data curation, automatic annotation, simulation and synthetic data. In this role as DL engineer, your goal is to build the most efficient and scalable DL pipeline possible, and train neural networks on global scale perception datasets. As a DL engineer your scope of tasks will be broad – training neural networks is the goal of those tasks – but not the sole task. 

Your mission and day-to-day tasks

You’ll be part of an autonomous development team with a lot of freedom and responsibility that through various tasks contributes to a shared DL platform, trains networks and ensures getting the needed data. A team that understands what to do, understands the performance of the networks and brings networks/algorithms to production. You’ll be working end to end with deep learning, tasks include for instance: 

• Contribute to the development of common training frameworks and data pipelines in a shared codebase.

• Engage with stakeholders to formulate your design goals, agree on interfaces and requirements.

• Be able to transition between different tasks depending on the current need.

• Train more junior engineers.

• Contribute to data needs, write annotation guidelines, curate data and ensure continuous data quality.

• Implement algorithms, define networks and objectives, innovate and experiment

• Define KPIs and build necessary metrics and evaluation pipelines

• Deploy, test and maintain your algorithms in production vehicles and on our compute cluster

Qualifications & experience

We’re looking for hands-on experience of both Deep Learning and Computer Vision. Most likely you have several years experience. Importantly you have a thorough understanding, knowledge and interest in Deep Learning and Computer Vision. You’re a really talented and clever person, with high capacity for new information, who easily learns new things. You have a can-do attitude and enjoy taking on different tasks depending on what is needed at the time. You have a sense of responsibility for the greater picture, you have an analytical mind and enjoy problem solving. You’re also an active listener and can be both humble and respectful as well as engage in dialogue around ideas. And you enjoy spreading your knowledge to others.

You have the following competencies:

• DL-based and classical computer vision. Including camera sensors and camera models.
• Software development in embedded systems
• Data engineering
• Architectural understanding
• Statistics, geometry
• DL frameworks (TensorFlow, PyTorch)
• Perception, including sensing, sensor fusion and tracking (vision, camera)
• Python, C/C++
• SQL

You might also have come across some: 

• Convolutional Networks, Transformers, Recurrent neural networks
• Data curation, active learning and auto annotation
• MLOps, compute orchestration, pipeline management and databases
• Simulation, synthetic data and neural radiance fields (NeRFs)
  

What more do we offer?

Flexible-remote way of working: Zenseact has a flexible and modern approach, thus is happy to offer to its employees the possibility for a combination of work at the office and from home. This doesn't include fully remote work from outside Sweden/China.

More about Zenseact

Our software makes a difference.
Using AI-based technology to create the ultimate driver support, we’re fighting to end car accidents and make roads safe for everyone. Every year, around 1,4 million people die in traffic while approximately 50 million people get injured. Many get disabled as a result of their injury. We can do better.

One purpose, one product.
We’re a software company dedicated to revolutionizing car safety. By designing the complete software stack for autonomous driving and advanced driver-assistance systems, we’re fighting to end car accidents and make roads safe for everyone. Zenseact was founded by Volvo Cars, and the teams are based in Gothenburg, Sweden, and Shanghai, China. When we aim for zero accidents faster, we strive to speed up the transition to safe automation. This is essentially achieved by making cars updatable – like a computer or a phone. With regular software updates, a vehicle can be made safer long after its production. By accelerating improvement loops, shortening development cycles, and deploying high-capacity software quickly, we can make cars safer, faster.

Culture with people at heart
To achieve our mission of saving lives and ending traffic accidents is to go where nobody has before. It requires us to venture into the unknown, pioneering new technology and pushing the frontier of autonomous driving. While there’s no denying our determination and expertise, we must stand united to succeed. By fostering a culture of support and enablement – a place of psychological safety where all of us can thrive – everything else will follow. We call this a people-at-heart culture. This culture means caring. It means the company cares about me, and we care about one another. It means sharing, so we give each other energy and have fun together. Our culture is also about belonging. It’s important to feel at home and that we can be ourselves at work. Finally, a people-at-heart culture means well-being. So, we enjoy the flexibility needed to be and do our 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.