Neko Health is a Swedish healthcare technology company co-founded in 2018 by Hjalmar Nilsonne and Daniel Ek. Neko's vision is to shift healthcare from reactive treatment toward preventative health and early detection. This requires completely reimagining the patient's experience and incorporating the latest advances in sensors and AI. Neko Health has developed a new medical scanning technology concept to make it possible to do broad and non-invasive health data collection that is convenient and affordable for the public. The company is based in Stockholm, offering the Neko Body Scan experience at locations in Stockholm, London and Manchester, with over 500 employees.

The Role

We are looking for a Machine Learning Engineer at Neko Health. In this role, you will be responsible for developing, shipping, and maintaining algorithms and Machine Learning models at Neko Health. This is a high-impact role, that will have impact and collaboration across all business streams.

You Will

• Design, develop, and optimize algorithms and machine learning models in collaboration with data scientists, software engineers, and domain experts. Ensure algorithms are robust and production ready
• Develop and optimize scalable ML pipelines for efficient training, validation, and deployment. Collaborate with engineering teams to integrate models into products and ensure performance meets SLAs through monitoring, alerts, on-call support, and timely fixes
• Take responsibility for best practices and state-of-the-art technologies within ML Engineering and establishing patterns that Data Scientists can follow
• Work cross-functionally with clinicians, researchers, and engineers to ensure algorithms and ML solutions align with real-world needs. Communicate technical concepts effectively to non-technical stakeholders

You Have

• A degree in Computer Science (ideally with a Machine Learning specialization), or a related field (MSc, or PhD)
• Strong experience in software engineering, with expertise in designing and deploying algorithms and ML systems
• Strong problem-solving skills and ability to work in cross-functional teams
• Deep expertise in software and ML engineering, with strong experience in C++, Python, and TensorFlow/PyTorch
• Expertise in ML model development, deployment, and monitoring (MLOps)
• Experience with cloud platforms and distributed computing

About The Engineering Team Distributed and Remote First We are nearly 100 full time engineers at the company, working from Berlin, Chamonix, Hamburg, Lisbon, Marseille, Vilnius, and Stockholm, spanning diverse disciplines such as Hardware Engineering, Firmware Development, Electrical Design, Algorithm Development, Machine Learning Development, Optronics Research, Frontend Development and more. We don't expect people to join us with a specific tech knowledge, but we do expect you to work with our tools. We use a mix of React, Typescript, C++, and Python. Our APIs are written in C# with ASP.NET Core, uses Azure Cosmos DB, and Azure Active Directory for authentication.

Our headquarters and our hardware development team are in Stockholm, Sweden.

We are a Remote First company; however, it is of course much easier to work remotely as a software engineer than a hardware or firmware engineer (since they require access to hardware or devices occasionally). Software engineers based in Stockholm work maybe one day a week or one day every two weeks from the office.

We meet a couple of times per year to get to know each other and have fun.

Organization and Way of Working The engineering team is divided into smaller cross functional project teams that each focus on a specific goal or target, where some groups are long-lived, and some are short-lived, depending on how big the goal or deliverable is. We strive to create groups which are cross-functional and able to complete their goals without dependence on other teams, even though this is of course not always possible.

Groups track goals on a yearly and quarterly basis with goal follow-up across the entire engineering organization on a bi-weekly basis. Most groups do internal planning on a bi-weekly basis, but in the end it's up to the group to decide how they want to work.

We have, however, mandated that all groups must present their progress or failures or hacks at our bi-weekly engineering demo, a fun meeting/presentation where we talk about everything from short-circuiting power-modules, how hard it is to calibrate cameras or align polygons in space, to neat new command line tools for operations, a new auth mechanism in the backend, a cool new way to visualize health data or a new feature which helps our doctors be more productive.

We have a flexible workplace that focuses on work/life balance, and we strongly believe in our mission but do not think that achieving it requires sacrificing everything else.