Machine Learning Engineer - Backend
Mission
At Neko Health, our mission is to deliver proactive healthcare for all—empowering members to take control of their health through cutting-edge technology and compassionate care.
Role Purpose
As a Machine Learning Engineer focused on Backend Services within the Data Science Platform team, you will enable robust, reliable, and responsible machine learning workflows powered by high-volume data from proprietary sensors and devices. You will design and operate scalable ML systems, backend services, and inference platforms using modern tooling and cloud-native approaches, supporting diverse machine learning use cases across Skin, Cardio, and beyond.
What You’ll Deliver in the First 6–12 Months
• Build and productionize reusable ML platform components supporting scalable and reliable machine learning workflows.
• Design and optimize backend services for real-time ML inference workloads, improving performance and reliability.
• Establish robust and monitored ML systems aligned with healthcare-grade reliability and compliance requirements.
• Deliver production inference workflows enabling timely and reliable results for Neko members.
• Collaborate across platform, data, and clinical teams to support scalable ML deployment across multiple domains.
Responsibilities
• Build reusable and scalable components supporting Machine Learning operations and workflows.
• Own and maintain Machine Learning systems and platform services.
• Optimize backend systems for real-time ML inference and high-throughput workloads.
• Collaborate with Platform and DevOps teams to ensure systems are resilient, observable, and fault-tolerant.
• Ensure backend and ML systems comply with healthcare and data privacy regulations.
• Design and maintain production inference pipelines delivering reliable and timely outputs.
• Work cross-functionally with Clinical Researchers, Data Scientists, and Engineers across multiple ML use cases.
Minimum Qualifications
• Strong programming skills in Python with experience building backend services (e.g. FastAPI).
• Advanced knowledge of production Machine Learning tools, systems, and practices.
• Deep understanding of distributed systems, microservices architecture, and API design.
• Familiarity with ML lifecycle tooling such as MLFlow, Kubeflow and orchestration frameworks like Dagster or Airflow.
• Experience with containerization and infrastructure tooling including Docker, Kubernetes, and Terraform.
• Experience working with cloud platforms (preferably Azure) and CI/CD pipelines.
• Ability to operate within complex ecosystems spanning medical domain, regulatory requirements, hardware, firmware, and sensor data.
• Strong judgment navigating evolving tooling landscapes and applying the right solutions to real-world problems.
About the Engineering Team
Distributed and Remote First
Neko Health has nearly 100 full-time engineers working across Berlin, Chamonix, Hamburg, Lisbon, Marseille, Vilnius, and Stockholm, spanning disciplines such as Hardware Engineering, Firmware Development, Electrical Design, Algorithm Development, Machine Learning, Optronics Research, and Software Engineering.
Our technology stack includes React, TypeScript, C++, Python, and C# with ASP.NET Core. We use Azure Cosmos DB and Azure Active Directory for authentication.
We are a Remote-First company, though some hardware and firmware roles require occasional access to physical devices. Software engineers in Stockholm typically work from the office once every one to two weeks. Teams meet in person several times per year for collaboration and team connection.
Organization and Way of Working
Engineering teams are structured into small, cross-functional groups aligned to specific goals. Some teams are long-lived while others are formed for targeted initiatives. Teams aim to operate autonomously while collaborating across the organization when necessary.
Goals are tracked quarterly and annually, with bi-weekly organization-wide progress reviews. Most teams operate on a bi-weekly planning cadence, though each group has flexibility in how they work.
All teams present progress, learnings, and experiments during bi-weekly engineering demos, covering topics ranging from hardware and calibration challenges to infrastructure improvements, backend capabilities, and data innovations that enhance clinical productivity.
Neko Health supports a flexible workplace that prioritizes work-life balance. We are deeply committed to our mission while believing meaningful impact should not require sacrificing personal wellbeing.
Hiring Process
Candidates progress from application and structured screening through thoughtfully designed interviews culminating in a formal offer and final pre-employment checks before joining the team.
Equal Opportunity & Inclusion Statement
Neko Health is committed to inclusive hiring and member-first care. We welcome candidates from all backgrounds and encourage you to request reasonable adjustments to support your application.
