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Machine Learning Engineer H/F

Date: 06-Apr-2021

Location: Lyon, FR

Company: Konecranes

At Konecranes, we believe that great customer experience is built on the people behind the Konecranes name – people committed to providing our customers with lifting equipment and services that lift their businesses. Everything we do, we do with passion and drive. 

We believe diversity drives business success and is the foundation for our growth. We welcome different backgrounds and skills that enrich our community and we promote a place where we can ALL be ourselves. This is what makes Konecranes a unique place to work.

 

 

The Data Science Lab team is looking for an enthusiastic and curious Machine Learning Engineer to complete our current roster.

 

Your main mission is to focus on the deployment and monitoring of machine learning models developed by data scientists. You will also collaborate with the Data Engineering Team located in Finland to put into production our predictive models and to follow up and track the data drift and model drift over time.

 

We are seeking a team player with excellent interpersonal skills with logical and emphatic problem-solving skills to drive projects into completion. The successful candidate will have a track record of deploying Artificial Intelligence products and managing their lifecycle, especially the integration and the monitoring.

 

Reporting to the Data Science Lab Director, your main tasks will be :

 

  • Manage the design, development, implementation and maintenance of AI products deployment solutions in the business applications.
  • Responsible of monitoring AI products deployed in Konecranes.
  • Interacting with data engineering team for the AI solutions industrialization.
  • Challenging and solving technical issues during the deployment and maintenance of our predictive models in Konecranes ecosystem.
  • Collaborating with data scientists to create a production ready code.
  • Identify and implement internal process improvements, such as automating manual processes, optimizing data delivery.
  • Anticipating issues and risks on projects.
  • Following up the latest technology development in the field of Data Science, monitoring solutions, tools and MLOps methodology.
  • Communicating advancement of projects and issues encountered to the director of the DSL.

 

Your profile / Qualifications : 

 

  • Master degree in applied statistics, mathematics/informatics, computer science, data science or AI with an experience at least of 3 years in Data Science field
  • Proven track record on former AI project deployment
  • Good experience to put into production data science projects, especially the monitoring of predictive model performance and usage over time
  • Capability to write production ready code
  • Deep understanding and hands-on experience of MLOps and Machine learning lifecycle management
  • Good understanding of machine learning techniques such as neural networks, NLP (Natural Language Processing), classification, clustering, forecasting and random forests etc.
  • Strong experience in programming languages – Python, Spark & SQL etc.
  • Experience on Microsoft Azure Cloud Platform and Databricks
  • Good knowledge of Azure DevOps (CI/CD), Docker and Kubernetes
  • Relational skills with team spirit
  • Fluent in English is mandatory (official work language)

 

Additional Qualifications :

  • Previous experience working in a matrix organization
  • Experience in digital products maintenance
  • Agile way of thinking/working
  • Power BI

 

 

 

 

Konecranes is a world-leading group of Lifting Businesses™, serving a broad range of customers. We are truly a global company with 16,900 employees at 600 locations in 50 countries. For over 80 years, we have been dedicated to improving the efficiency and performance of businesses in all types of industries. We believe that sustainable growth is a result of a strong responsible performance. Konecranes is committed to ensuring that all employees and job applicants are treated fairly in an environment which is free from any form of discrimination.