ML Ops Engineer

Neko Health; Stockholms kommun; Hybrid; SEK 1,087,784 - 1,631,676; Full time

Job summary

Neko Health in Stockholm is seeking a Lead Machine Learning Engineer to enable robust machine learning workflows at scale. This role focuses on building and operationalizing production-grade ML systems using proprietary data from sensors and technologies.

You will collaborate with various teams to enhance the adoption of scalable ML practices and ensure compliance with healthcare standards. Candidates should possess strong programming skills and experience with ML systems.

Qualifications

• Strong programming skills in Python with a solid understanding of Machine Learning concepts.
• Experience building end‑to‑end production ML systems and platformisation initiatives.
• Knowledge of PyTorch, Kubernetes, Terraform, distributed systems, and ML orchestration tools.
• Advanced understanding of production Machine Learning tools and best practices.
• 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.

Responsibilities

• Build reusable and scalable components supporting Machine Learning operations and platformisation.
• Own and maintain Machine Learning systems and platform services.
• Establish and promote best practices across experiment tracking, model lifecycle, and evaluation.
• Design and maintain production inference workflows delivering reliable and timely outputs.
• Collaborate cross‑functionally with Clinical Researchers, Data Scientists, ML Engineers, and Data Engineers.
• Ensure ML systems and workflows align with healthcare and data privacy requirements.

Skills

Strong programming skills in Python

Machine Learning concepts

End-to-end production ML systems

Knowledge of PyTorch

Kubernetes

Terraform

Distributed systems

ML orchestration tools

Tools

Python

C++

React

TypeScript

C#

ASP.NET Core

Azure Cosmos DB

Job description

Mission: Neko is redefining what prevention means, from treating illness when it arrives, to sustaining health before it is ever at risk. Our mission is to make data‑driven, preventative care accessible to more people, before symptoms appear.

In a single, non‑invasive visit under an hour, proprietary technology and direct clinical care combine to deliver personalised, actionable insights. It is a team that thinks in 10x, not 10%. Every role here plays a part in building a world where prevention is the norm, and where your work genuinely helps people live longer, healthier lives.

Role Purpose

As a Lead Machine Learning Engineer focused on MLOps within the Data Science Platform team, you will enable robust, reliable, and responsible machine learning workflows at scale. Working with high‑volume data from proprietary sensors and devices, you will design and operate production‑grade ML systems, ensuring strong experiment tracking, model lifecycle management, and scalable deployment across multiple healthcare domains.

What You’ll Deliver in the First 6–12 Months

• Build and productionise reusable MLOps components supporting scalable and reliable ML workflows.
• Establish strong ML lifecycle practices including experiment tracking, evaluation, and reproducibility.
• Enable robust and monitored ML systems aligned with healthcare‑grade reliability and compliance requirements.
• Deliver reliable production inference workflows powering real‑world outcomes for Neko members.
• Partner across data, platform, and clinical teams to support scalable ML adoption across multiple use cases.

Responsibilities

• Build reusable and scalable components supporting Machine Learning operations and platformisation.
• Own and maintain Machine Learning systems and platform services.
• Establish and promote best practices across experiment tracking, model lifecycle, and evaluation.
• Design and maintain production inference workflows delivering reliable and timely outputs.
• Collaborate cross‑functionally with Clinical Researchers, Data Scientists, ML Engineers, and Data Engineers.
• Ensure ML systems and workflows align with healthcare and data privacy requirements.

Minimum Qualifications

• Strong programming skills in Python with a solid understanding of Machine Learning concepts.
• Experience building end‑to‑end production ML systems and platformisation initiatives.
• Knowledge of PyTorch, Kubernetes, Terraform, distributed systems, and ML orchestration tools.
• Advanced understanding of production Machine Learning tools and best practices.
• 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

We have nearly 160 full‑time engineers working across our hubs in Stockholm, London, and Berlin, spanning disciplines including Hardware Engineering, Firmware Development, Electrical Design, Algorithm Development, Machine Learning, Optronics Research, and Frontend Development. We expect you to work with our tools: React, TypeScript, C++, and Python. Our APIs are written in C# with ASP.NET Core, using Azure Cosmos DB and Azure Active Directory for authentication.

Our headquarters and hardware development team are based in Stockholm. We work hybrid, with engineers typically in the office 1‑2 days a week. Hardware and firmware engineers need occasional on‑site access to devices; software engineers have more flexibility. We come together as a full team a couple of times a year.

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, with each group having 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 prioritises work‑life balance. We are deeply committed to our mission while believing meaningful impact should not require sacrificing personal well‑being.

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.

Compensation Range: €100K - €150K