Machine Learning Engineer

4w4 weeks ago

H&M Group

Stockholm, SE · Full-time · SEK 600,000 – SEK 800,000

About this role

As a Machine Learning Engineer at H&M Group, you will implement, test, and maintain AI/ML solutions that ensure reliable, scalable, and high-quality production-grade deliveries. You will contribute to the design and refinement of AI/ML features and services in collaboration with more experienced engineers.

Your day-to-day involves participating in development activities such as code reviews, testing, and monitoring to ensure product quality, maintainability, and performance. You will troubleshoot and resolve software, infrastructure, or data-related issues within existing AI/ML solutions.

You will be part of a cross-functional product team with other ML engineers, data scientists, data analysts, and a product manager. You will collaborate with business stakeholders, solution architects, and engineering managers to build and enhance AI-powered solutions that drive innovation and efficiency across H&M.

You will contribute to continuous improvement initiatives by suggesting enhancements to processes, tooling, and engineering best practices. Staying updated on emerging AI/ML technologies, tools, and ways of working will help you continuously strengthen engineering capabilities.

Requirements

Strong Python programming skills and experience with tools, frameworks, and technologies relevant to AI/ML development.
Solid understanding of software engineering principles, testing methodologies, and best practices for building maintainable software solutions.
Experience with cloud technologies and cloud-based AI/ML development, preferably on GCP and with Vertex AI.
Thorough understanding of AI/ML algorithms, development lifecycle, MLOps practices, and production-grade AI/ML solution development.
Strong problem-solving skills and ability to troubleshoot software, infrastructure, and data-related issues.
Practical experience in working with version control systems such as Git and Agile development practices.
Strong collaboration and communication skills, with the ability to work effectively across cross-functional teams and communicate technical topics to both technical and non-technical stakeholders.
Ability to contribute to requirement analysis and translate business needs into technical implementation tasks together with more experienced engineers.

Responsibilities

Implement, test, and maintain AI/ML solutions that ensure reliable, scalable, and high-quality production-grade deliveries.
Contribute to the design and refinement of AI/ML features and services in collaboration with more experienced engineers.
Participate in development activities such as code reviews, testing, and monitoring to ensure product quality, maintainability, and performance.
Troubleshoot and resolve software, infrastructure, or data-related issues within existing AI/ML solutions.
Collaborate with peers and stakeholders to clarify requirements and translate business needs into technical implementation tasks.
Contribute to continuous improvement initiatives by suggesting enhancements to processes, tooling, and engineering best practices.
Stay updated on emerging AI/ML technologies, tools, and ways of working to continuously strengthen engineering capabilities.