How would it feel to work at the cutting edge of Deep Learning together with other highly skilled engineers and researchers with sharp minds, from all over the world – and get access to one of the largest GPU clusters in Sweden? And how would you feel being the enabler of bringing groundbreaking ideas to cars driving in the streets in the shortest time possible? 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.

Zenseact develops world-leading safety software for Volvo Cars, and Deep Learning is at the core of everything Zenseact is. We have the arguably hardest Deep Learning use case out there – autonomous driving, 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’re ramping up significantly, expanding our compute infrastructure and having acquired one of the biggest GPU compute clusters in Scandinavia. We're looking for proficient people to add to our experienced Deep Learning teams and form new teams to introduce Deep Learning to more parts of our software stack. We have an established capability to integrate a fully in-house developed "pixel to torque" ADAS software into consumer vehicles, and in the next step aim to build an automotive perception and planning system rivaling the industry's best.

Insights from the team

As an MLOps engineer, your goal will be to establish processes and build tooling for producing neural networks trained on global scale automotive perception datasets. The team is focused on ensuring the perception neural networks are consistently prepared for inclusion in the product as part of the cars' onboard software. As a member of this team, you will be a major enabler for DL development. You will work closely with:

• Teams in the MLOps area, together ensuring the flow of models from training to deployment in the car;
• DL perception teams, providing them with tools, services, and automation, helping build fundamental training and validation procedures, and ensuring training speed and reliability;
• DevOps and IT teams, connecting the DL workflows to the Zenseact's hardware infrastructure and CI/CD pipelines.

Your mission and day-to-day tasks

• Ensure continuous training of the perception models. Define the training schedule, maintain the stability of the trainings through CI testing, monitor and improve training speed and resource usage.
• Provide full observability of the model KPIs, including evolution of the metrics over time, granular metric breakdown, low-level metrics of the trained model, high-level metrics of the deployed and integrated model, etc.
• Establish versioning of trained models and training and validation datasets.
• Enable full lineage tracking of the models deployed in the test and customer vehicles to the data, configuration parameters and code used for training.
• Provide a centralized platform for experiment tracking.
• Assist DL teams with workflow automation.

What’s in it for you

• Work at the forefront of tech in one of Sweden’s biggest and most interesting, challenging and dynamic AI/ML-companies.
• Collaborate with highly skilled, innovative, creative and smart people.
• Work with people from all over the world, close to what science just came up with.
• Enjoy a flexible work approach and a genuinely good work/life balance.

Qualifications & experience

We're looking for engineers with minimum 4 years of experience in Deep Learning and software engineering combined - whereof minimum 2 years of Deep Learning experience - outside of school.

It is essential that you possess a comprehensive understanding, knowledge, and enthusiasm for Deep Learning, alongside familiarity with operational topics. You show a remarkable ability to engage with new concepts and incorporate them into your work. You have a willingness to contribute 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 investigating mindset 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 build connections with other teams and areas.

Essential experience

• Software engineering (Python)
• Experience with DL model development (launching experiments, evaluating metrics, speeding up trainings, debugging crashes, ...)
• Proficiency with DL frameworks and tools (TensorFlow, PyTorch, TensorRT, ONNX, ...)
• Interest for process automation, optimization, and observability

Nice to have

• Hands-on experience establishing the MLOps cycle
• Familiarity with DL lifecycle management tools (W&B, MLFlow, ClearML, ...)
• Experience with container technologies (Docker, Singularity, Kubernetes)
• Knowledge of best software architecture practices
• Thorough understanding of Convolutional Networks, Transformers, Recurrent Neural Networks

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 and Lund, Sweden, Munich in Germany 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, and faster.

Culture with people at heart
To achieve our mission of saving lives and ending traffic accidents we must 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 continuously, so we highly recommend that you submit your application at your earliest convenience.