Machine Learning Engineer AI, Advanced Analytics & Data

  • Liljeholmsstranden 5, 117 43 Stockholm, Sweden
  • Full-time
  • Department: H&M Group

Company Description

We are on an exciting journey to meet and exceed our customers' expectations today, tomorrow and in the future. Rapid technological development and new customer behaviours are transforming the fashion retail industry. To cater the individual needs and desires of our millions of customers, Business Tech delivers technological solutions for the entire value chain for all our brands.

Job Description

We are now looking for a Machine Learning Engineer to bring in new competence to our new organization Business Tech.

We are on a journey together which means there is no clear path. You will play an important role in setting the foundation and creating our future organisation, Furthermore, you will:

  • Pairing with Data Scientists, develop machine learning software product 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 also scale out to the comprehensive fashion network of H&M
     
  • Design, develop and maintain the large-scale data infrastructure required for the machine learning projects
     
  • Leverage on understanding of software architecture and software design patterns to write scalable, maintainable, well-designed and future-proof code
     
  • Develop tool and framework to address common needs in machine learning project like model traceability, feature reuse, A/B test, etc.
     
  • Work in cross-functional agile team of highly skilled engineers, data scientists, business stakeholders to build the AI ecosystem within H&M

Qualifications

Our journey will lead to something new and exciting - we will test, fail and learn. You are an important player in this transformation; therefore, we believe you are flexible, stress-resistant and able to work in an environment that is not yet formalized. 

Who you are:

·   have a degree within software engineering or similar field (e.g. computer science and programming) and a strong will to continuously develop your engineering skillset 

·   are a hands-on person, love coding as much as breathing and would like to deploy software engineering practice into machine learning projects.

·   have at least 2 plus years of working experience in developing machine learning products

·  are experienced in one of following programming languages:  Python, Scala or Java. Experience in Spark and distributed computing is seen as a merit. 

·   have experience with handling high volume heterogeneous data (both batch and stream) and good understanding about data storage and data structure would be a big plus 

·   have experience in agile environment, team collaboration, data-driven development, reliable and responsible experimentation 

Do you think we are a match? We hope so!

This is a fulltime position with placement in Stockholm.  Please apply with CV and Cover Letter (English) as soon as possible. Due to GDPR, we do not accept applications via email. 

FYI, during July, we will because of summer holidays have a pause in our recruitment processes and will take them up again when we are back in mid August. 

Additional Information

The H&M group is on an exciting journey to meet and exceed our customers' expectations today, tomorrow and in the future. Rapid technological development and new customer behaviors are transforming the fashion retail industry. To cater the individual needs and desires of our millions of customers, Business Tech will deliver technological solutions for the entire value chain for all our brands.  

In Business Tech, we will continuously surprise and delight our customers and accelerate our business - by releasing the power of people, data and technology. We explore new ways of working, have a customer focused mindset, embrace our strong values and release the power of our people to innovate and develop products that make a meaningful impact to customers all over the world 

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