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Tech Lead Machine Learning Data Engineer - Recommendations (Remote, Israel)

Full-time
Remote in EMEA
Apply now

Tech Lead Machine Learning Data Engineer - Recommendations (Remote, Israel)

About the role

  • Leading engineering solutions for product recommendations engine using the billions of Shopify’s catalog’s products
  • Designing, architecting and developing tools, scripts and pipelines for serving and ingesting data at scale
  • Optimize for performance and emphasize on observability
  • Using test-driven development to write well-tested code
  • Fixing bugs fast and taking your time to solve hard problems well

Qualifications

  • Hands-on experience in search/personalized recommendation/advertising or related fields
  • Deep understanding of recommender system business, with specialization in one or multiple areas: ranking, reall, user profiling, content understanding
  • Experience building highly scalable, performant data solutions (ETL/ELT/ML)
  • Professional - not compromising on high quality code, keeps up to date with latest methodologies and solutions
  • A strong foundation of design principles, especially when it relates to platform development in the areas of API, data modeling, and scale
  • Curiosity and passion to constantly learn new things; Shopify changes fast, and we need the people who work here to be able to change and learn fast too
  • Passion for AI, Machine Learning and data at scale
  • Experience with executing Machine Learning models is a plus

A Staff (Lead) Data Engineer would typically have 6-10 years of experience in one or more of the following areas:

  • Experience with the internals of a distributed compute engine (Spark, Presto, DBT, or Flink/Beam)
  • Experience in query optimization, resource allocation and management, and data lake performance (Presto, SQL)
  • Experience with cloud infrastructure (Google Cloud, Kubernetes, Terraform)
  • Experience with security products and methods (Apache Ranger, Apache Knox, OAuth, IAM, Kerberos)
  • Experience deploying and scaling ML solutions using open-source frameworks (MLFlow, TFX, H2O, etc.)
  • Experience building full-stack applications (Ruby/Rails, React, TypeScript)
  • Background and practical experience in statistics and/or computational mathematics (Bayesian and Frequentist approaches, NumPy, PyMC3, etc.)
  • Modern Big-Data storage technologies (Iceberg, Hudi, Delta)

 

We know that looking for a new role can be both exciting and time-consuming, and we truly appreciate your effort. Stephanie is an actual real live person (👋🏻) and is looking forward to learning more about you and your interest in joining our team.

Application Timeline:

As there are multiple positions, this posting will remain live until all positions have been filled. Successful candidates can expect to hear back from us within 2 weeks of application

#LI-REMOTE #LI-SH2

Shopify is now permanently remote, and we’re working towards a future that is digital by design. That location you see above? Consider it merely an example of hundreds of potential locations Shopify is hiring. Learn more here: https://www.shopify.com/careers/work-anywhere

Our belief is that a strong commitment to diversity & inclusion enables us to truly make commerce better for everyone. We encourage applications from Indigenous peoples, racialized people, people with disabilities, people from gender and sexually diverse communities, and/or people with intersectional identities. Please take a look at our Sustainability Reports to learn more about Shopify’s commitments to our communities, and our planet.

At Shopify, we understand that experience comes in many forms. We’re dedicated to adding new perspectives to the team - so if your experience is this close to what we’re looking for, please consider applying.

How we hire

At Shopify, we put a lot of care and time into who we hire. We believe that in order to build the best products, we need to build high impact teams. Our recruitment process centres around what we call the Life Story interview, a conversational-style interview where we get to learn more about you.
Learn more about our hiring process 
Apply now