Machine Learning Engineer
Machine Learning Engineer
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Job Description
JOB DESCRIPTION
At Levi Strauss & Co we are revolutionising the apparel business and redefining the way denim is made.We are taking one of the worlds most iconic brands into the next century: from creating machine learningpowered denim finishes to using blockchain for our factory workers wellbeing to building algorithms to better meet the needs of our consumers and optimize our supply chain.
Be a pioneer in the fashion industry by joining our Digital and Technology organization where you will have the chance to build exciting solutions that will impact our global business and at the be part of large and diverse data community.
The Data Science analytics and AI team at Levis is responsible of building datadriven solutions that improve our existing business processes in multiple areas across supply chain retail revenue management and ecommerce among others. The team is responsible for the endtoend solution development from data ingestion until operationalisation of models in production. As a Machine Learning Engineer within this org you will work alongside Data Scientists Analysts ML engineers and product management to operationalise our ML models in production on a broad set of domains powering a datadriven transformation of our standard business procedures across channels and organizations. You will develop and deploy novel approaches to optimize existing machine learning systems to maximise their value and increase consumer satisfaction at every brand touchpoint. We need someone who will bring thoughtful solutions perspective empathy creativity and a positive attitude to solve the different challenges in our business.
You are a team player always willing to work alongside and support your colleagues you have a proactive and selfdriven mindset towards problemsolving looking to take on challenges and the opportunity to grow and you are able to effectively balance solution vs risk taking.
Key responsibilities:
Work with data scientists analysts ML engineers and product management to create and deploy new models and ML systems.
Implement endtoend solutions across the full breadth of ML model development lifecycle. The specific role includes working hand in hand with the scientists from the point of data exploration for model development to the point of building features ML pipelines and deploying them in production. You will have an opportunity to work on both batch and real time models. The role also involves operational support.
Identify new opportunities to improve existing solutions towards greater accuracy and/or efficiency
Establish scalable efficient automated processes for data analyses model development validation and implementation
Write efficient and scalable software to ship products in an iterative continualrelease environment
Write optimized data pipelines to support machine learning models
Contribute to and promote good software engineering practices across the team and build cloud native software for ML pipelines
Contribute to and reuse community best practices
Example Projects
Besides driving the transformation of Levis into a datadriven enterprise in general here are some specific projects you will work on and contribute to:
Pricing elasticity modelling and pricing recommendations
Promotional campaigns optimization and discounts recommendations
Analytics solutions to support revenue management activities
About You
University or advanced degree in engineering computer science mathematics or a related field
3 years experience developing and deploying machine learning systems into production
Expertise in data engineering analysis and processing (e.g. designing and maintaining ETLs validating data and detecting quality issues)
Previous experience developing predictive models in a production environment MLOps and model integration into larger scale applications.
Experience working with big data tools: Spark Hadoop Kafka etc.
Experience with at least one cloud provider solution (AWS GCP Azure) and understanding of serverless code development. GCP experience preferred.
Efficiency with objectoriented/object function scripting languages Python .
Efficiency with Python datahandling libraries like Pandas or Pyspark.
Efficiency in SQL for data consumption and transformation. Nice to have: SparkSQL BigQuery SQL dialects.
Expertise in standard software engineering methodology e.g. unit testing test automation continuous integration continuous deployment code reviews design documentation
Working experience with native ML orchestration systems such as Kubeflow Vertex AI Pipelines Airflow TFX...
Relevant working experience with Docker and Kubernetes is a big plus.
LOCATION
Barcelona SpainFULL TIME/PART TIME
Full timeCurrent LS&Co Employees apply via your Workday account.
Employment Type
Full-Time
