Machine Learning Engineer

Arbetsbeskrivning

Bring your ideas to work where we’re all about bringing ideas to life.
By creating desirable solutions and great experiences that enrich people’s daily lives and the health of our planet, we want to be a driving force in delivering enjoyable and sustainable living. We go to work every day determined to shape living for the better – for our customers and for the health of our planet.
For that, we employ great people from a wide variety of backgrounds – not just because it’s the right thing to do, but also because we believe that diverse perspectives make our business stronger and more innovative. If you share our values, come find your place in our global community. Meet us on @lifeatelectrolux and career.electroluxgroup.com to learn more.
You will be based at Electrolux HQ in Stockholm at Kungsholmen. Our Headquarters in Stockholm is an amazing and unique place to work and grow! Over 1000 professional and 75+ nationalities shape living for the better every day.
Your job is to operationalize machine learning solutions into scalable reliable products using state-of-the-art ML-ops technologies. It also includes architecting and implementing reusable machine learning frameworks. You will work closely with members of a cross-functional ML team ensuring that we deliver high quality solutions. You are also expected to advice and provide direction on ML-ops questions arising from product teams.
Your main tasks:
•In collaboration with data scientists, apply software engineering design and best practices to operationalize ML prototypes into scalable products
•Design and develop reusable frameworks to easily train, evaluate and serve ML models at scale
•Explore, build & maintain an ML-ops experimentation platform
•Advise during planning and solution assurance stages from an ML-ops solution point-of-view
Qualifications:
•3+ years machine learning engineering experience and B.Sc. in Computer Science (or equivalent)
•Solid programming experience with great software engineering best practices and strong knowledge of Python and SQL including related ecosystems and frameworks
•Experience with ML platforms, such as MLFlow, Spark and Databricks as well as ML pipeline development and their orchestration
•Distributed data processing such as Spark, BigQuery or Apache Beam
•Experience with DevOps and automated software development processes. Comfortable with technologies such as Docker, Kubernetes, etc.
•Solid experience of working in cloud (preferably Azure, but AWS/GCP also relevant)
•Good understanding of data structures and database technologies
The challenge - As an enterprise producing millions of appliances each year and counting more than 50.000 employees, Electrolux is already generating massive amounts of data in hundreds of systems across the globe, from supply chain to sales to sensors in smart home appliances. This offers a huge opportunity to facilitate and improve data-driven decision making.
The team - The Electrolux Global AI & Data Science team supports business functions across the entire company and helps them turning raw data into valuable insights and actions. The team is a key enabler to support the company's digital transformation and takes the role of being the center of excellence for data handling and advanced analytics within the company.
Find out more on:
https://www.linkedin.com/company/electrolux/life/lifeatelectrolux
https://www.linkedin.com/company/electrolux/life/sweden
Electrolux is a leading global appliance company that has shaped living for the better for more than 100 years. We reinvent taste, care and wellbeing experiences for millions of people, always striving to be at the forefront of sustainability in society through our solutions and operations. Under our brands, including Electrolux, AEG and Frigidaire, we sell approximately 60 million household products in approximately 120 markets every year. In 2020 Electrolux had sales of SEK 116 billion and employed 48,000 people around the world. For more information go to www.electroluxgroup.com.

Sammanfattning

Postadress

SANKT GÖRANSGATAN 143
Stockholm, 11217

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