Scaleout’s mission is to enable its customers to develop machine learning solutions without compromising on data ownership and privacy. Our main product is the Scaleout Edge platform – designed to orchestrate machine learning across edge-to-cloud. Being built natively for federated learning, our software helps developers tackle challenges like privacy, security, compliance, and data accessibility that inhibit AI adoption in mission-critical organizations. By bringing AI to the data, we enable our customers to train,deploy and govern AI models as close to the edge and data source as possible, be it on vehicles, drones, edge clouds, or industry robots. 

We are serving customers in mission-critical organizations, including defence, automotive and industrial IoT. As a member of the Scaleout team your research will have an impact by pushing the frontier of ML privacy, cybersecurity and embodied AI forward. Scaleout is supported by leading deep tech investors such as Navigare Ventures owned by Wallenberg Investments AB, Fairpoint Capital,  ALMI Invest, Uppsala University Invest and the Beijer Foundation.

Our team at Scaleout, made up of experts in data science, distributed systems and software engineering combines research expertise from top-ranked Uppsala University with business experience from companies such as Google, BCG and Viacom. You will be part of a team that combines the best from research with a clear focus on industrial impact. In our fast-paced, collaborative environment, we emphasize the value of continuous learning, knowledge-sharing and diverse perspectives. As we focus on helping companies in effectively adopting AI, every team member plays a crucial role in contributing ideas and influencing the company's direction. We provide an innovative environment where you can work on pioneering AI projects, particularly focusing on federated learning and adversarial machine learning, to drive significant advancements in the field. All this, while maintaining a strong commitment to data privacy and ethical AI practices.  

We offer a hybrid workplace. The successful candidate will have a home base in one of our office locations in Uppsala, Stockholm or Göteborg, and will be expected to be available for limited travel to customer facilities and to international conferences. 

We seek passionate individuals who are eager to tackle complex problems. You hold an advanced degree in machine learning, computer science, scientific computing or a related field. Experience in federated learning, software engineering and distributed computing are meriting. 

As a person, you thrive in a collaborative environment and feel excited about the opportunity to actively shape the next wave in machine learning, as well as driving the business forward by participating as an expert resource in technical pre-sales.

The successful candidate must be eligible to obtain and maintain a security clearance.

As a member of our machine learning team, your primary focus will be research and development in the project Redefining Space Data Infrastructure. You will be working closely with our engineering team to align development with our main product, the Scaleout Edge platform. 

The project, funded by the Swedish Space Agency and conducted in collaboration with industry stakeholders and Uppsala University, aims to revolutionize space-based services by developing a federated learning framework for dual-use satellite systems. We will implement smart filters using active learning to reduce data transmission from orbit and utilize federated learning to enable collaborative model training between LEO/GEO satellites and ground stations without raw data leaving its source. This will create a communication-efficient and privacy-preserving AI infrastructure for both civilian and defense applications. Key responsibilities include: 

• Design and develop AI-driven methods for collaborative learning in orbit.
• Implement active-learning-based smart filters to minimize data transmission.
• Develop and deploy federated learning systems for in-orbit collaborative model training.
• Work with real-world datasets, including CubeSat telemetry for anomaly detection and the xView dataset for object detection in satellite imagery.
• Contribute to strengthening C4ISR capabilities through on-orbit AI-driven data processing.

As a person you are passionate about bringing complex new technology to production. You will be expected to take a great deal of ownership and individual responsibility for driving the work forward and for ensuring that the results are delivering outcomes both for our customers and our business. 

You will also contribute to product development and our internal R&D, primarily to our toolkits and workflows realizing machine learning use-cases on top of the Scaleout Edge platform. We believe that you are a high-agency team player, prepared to get the job done also when it requires you to go outside of your technical comfort zone. While the main focus of this role is research on next-generation space data infrastructure, you will also be working closely with our customer engineering teams to accelerate development of AI use-cases on top of the Scaleout Edge platform.

The role will require limited travel, including international conferences.  

This role has the following set of required and optional qualifications.

Must have Qualifications 

• Experience with satellite communication systems or similar constrained environments
• Advance degree in machine learning, computer science or a related field. 
• Proficiency in programming in Python. 
• Strong communication skills. 

Meriting Qualifications

• In depth understanding of statistical machine learning.  
• Experience with active learning and federated learning. 
• Proficiency in developing and deploying machine learning models on edge devices. 
• Distributed systems and large scale storage systems. 
• Experience in defence, automotive or industrial IoT. 
• C/C++ 
• Software Engineering experience.  

The successful candidate must be eligible to obtain and maintain a security clearance.

Apply via LinkedIn, include a CV and a cover letter. Your cover letter should highlight your experiences and skills relevant to the job requirements, as well as your motivation for applying.

We look forward to learning more about you and exploring the potential fit with our team.