Machine Learning Engineer

The primary tasks for a senior level Machine Learning Engineer in MLE area are:
• Develop AI/ML software products including but not limited to explore large data set, try out new algorithms, feature engineering, test and evaluate model output, deploy the solution for production usage and scale out for a maintainable solution in the comprehensive fashion network of H&M.
• Design, develop and maintain the large-scale data infrastructure required for the AI/ML projects.
• Leverage on understanding of software architecture and software design patterns contributing to architectural decisions, technical roadmap planning, and to write scalable, maintainable, well-designed, and future-proof code.
• Develop solutions, components, services and frameworks to address both specific and common needs in AI/ML projects, like feature reuse, model traceability, monitoring, A/B test, versioning, release, and serving of both online inference end-points and batch inference.
• Work in cross-functional agile team of highly skilled engineers, data scientists, and business stakeholders - to build the AI ecosystem within the company.

Required skills and experiences:
• Have a BSc or MSc degree in computer science, engineering or related field, or equivalent practical experience.
• Have 5+ years’ professional experience working in relevant role(s) for a senior level Machine Learning Engineer.
• A hands-on person, with great software engineering skills, who loves coding, and like applying good software engineering practices and DevOps principals to machine learning and AI projects.
• Have experience in developing software products that have been successfully deployed to production and scaled in a bigger organization, also ensuring product quality, security and performance.
• Have several years of coding experience in modern programming languages, and strong background in Python programming, i.e. 4+ years.
• Have great hands-on experience with cloud technologies for ML development, preferably Google Cloud Platform, and also including Vertex AI.
• Have solid experience in MLOps practices, developing ML pipelines, data pipelines and deploying ML applications to production.
• Have a strong working knowledge of a variety of AI/ML techniques and experience working with different frameworks.
• Have experience handling and developing for high volume heterogeneous data (both batch and stream), preferably also including hands-on development in DBT, and have also a solid understanding of cloud data storage technologies and data quality.
• Have experience from aligning and analyzing requirement; driving design solutions; breaking down work into stories and tasks; supporting and mentoring team members; and making sure organizational standards and best-practices are implemented and followed.
• Familiar with agile ways of working, team collaboration and data-driven development.

Required cloud certification: GCP Professional Machine Learning Engine