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Machine Learning Engineer - Depop

Toronto, Ontario, Canada

Pay
CAD 142,400–190,100/year · BaseAnnual period assumed · Location-specific pay — pay source
The base pay range for this position is expected in the range below: C$142,400 - C$190,100 Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience. The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or other benefits (including RRSP eligibility, various paid time off benefits, such as PTO and parental leave). Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
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Work setup
Unconfirmed
Employment
Unconfirmed
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What you’ll bring

All qualifications

Core experience

  • Experience building large-scale distributed applications and proficiency in an object-oriented or modern programming language such as Java, Scala, or Python.
  • Experience working with NoSQL databases and key-value stores such as MongoDB or Redis.
  • Experience building and supporting scalable data and ML pipelines.
  • Experience with cloud platforms and cloud-native technologies.

Preferred experience

  • Experience with large-scale data processing technologies such as Spark or Hadoop is a plus.
  • Experience productionizing Machine Learning or AI models and building supporting infrastructure is a plus.
  • Experience with MLOps, model serving, monitoring, observability, and deployment automation is a plus.
  • Experience with Large Language Models (LLMs), GenAI, RAG, and prompt engineering is a plus.
Qualification wording
Experience building large-scale distributed applications and proficiency in an object-oriented or modern programming language such as Java, Scala, or Python.
Experience working with NoSQL databases and key-value stores such as MongoDB or Redis.
Experience building and supporting scalable data and ML pipelines.
Experience with cloud platforms and cloud-native technologies.
Experience with large-scale data processing technologies such as Spark or Hadoop is a plus.
Experience productionizing Machine Learning or AI models and building supporting infrastructure is a plus.
Experience with MLOps, model serving, monitoring, observability, and deployment automation is a plus.
Experience with Large Language Models (LLMs), GenAI, RAG, and prompt engineering is a plus.

Tools in this posting

  • Java
  • Scala
  • Hadoop
  • MongoDB
  • NoSQL
  • Spark
  • Python
  • Redis
Source — Tool mentions in context
- MS in Computer Science or a related field with 5+ years of relevant experience, or BS with 7+ years of relevant experience in Software Engineering, Machine Learning, AI, or a related discipline. - Experience building large-scale distributed applications and proficiency in an object-oriented or modern programming language such as Java, Scala, or Python. - Experience working with NoSQL databases and key-value stores such as MongoDB or Redis.
- Experience with cloud platforms and cloud-native technologies. - Experience with large-scale data processing technologies such as Spark or Hadoop is a plus. - Experience productionizing Machine Learning or AI models and building supporting infrastructure is a plus.
- Experience building large-scale distributed applications and proficiency in an object-oriented or modern programming language such as Java, Scala, or Python. - Experience working with NoSQL databases and key-value stores such as MongoDB or Redis. - Experience building and supporting scalable data and ML pipelines.

Job description

View original posting ↗

At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.

Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.

Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.

Depop is a peer-to-peer circular fashion marketplace where anyone can buy, sell and discover secondhand fashion. Our mission is simple: to make fashion circular by making secondhand as exciting and rewarding as buying new.

Founded in 2011, Depop’s diverse community has helped move resale into the mainstream, where buying secondhand is no longer an alternative, but how people of different ages now engage with fashion. Today, more than 56 million registered users come to Depop to find great value, express their own personal style and give clothes a longer life. We believe that everything you want already exists, and our role is to help people discover it. From everyday essentials to vintage and designer finds, Depop brings together a wide range of affordable styles in one place. It’s a marketplace where anyone can clear out their wardrobe or build a business, explore their style, and take part in a more circular way to shop.

Powered by a team of over 500 people, our company is headquartered in London, with offices in New York.

The Depop team is building intelligent, scalable experiences powered by the latest Machine Learning, AI, NLP, LLM/GenAI, and RAG technologies. We work with large-scale marketplace data and modern ML infrastructure to develop and productionize solutions that improve how millions of buyers and sellers interact with the Depop marketplace.

This is an opportunity to:

  • Influence how AI and Machine Learning shape the future of Depop's global marketplace and customer experience.

  • Work with large and unique datasets, including structured and unstructured marketplace data representing millions of users and items.

  • Develop and deploy state-of-the-art AI and ML models into production with direct, measurable impact on buyers and sellers.

  • Build and scale large data pipelines and distributed systems that support production ML applications.

  • Partner across engineering, product, data, and applied science teams to take ML solutions from experimentation through production.

  • Contribute to modern ML infrastructure, deployment, monitoring, and operational best practices at scale.

Qualifications

  • MS in Computer Science or a related field with 5+ years of relevant experience, or BS with 7+ years of relevant experience in Software Engineering, Machine Learning, AI, or a related discipline.

  • Experience building large-scale distributed applications and proficiency in an object-oriented or modern programming language such as Java, Scala, or Python.

  • Experience working with NoSQL databases and key-value stores such as MongoDB or Redis.

  • Experience building and supporting scalable data and ML pipelines.

  • Strong problem-solving skills with a willingness to learn and adopt new technologies as needed.

  • Experience with cloud platforms and cloud-native technologies.

  • Experience with large-scale data processing technologies such as Spark or Hadoop is a plus.

  • Experience productionizing Machine Learning or AI models and building supporting infrastructure is a plus.

  • Experience with MLOps, model serving, monitoring, observability, and deployment automation is a plus.

  • Experience with Large Language Models (LLMs), GenAI, RAG, and prompt engineering is a plus.

Additional Details

The base pay range for this position is expected in the range below:

C$142,400 - C$190,100

Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience. The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or other benefits (including RRSP eligibility, various paid time off benefits, such as PTO and parental leave). Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

This job posting relates to an existing vacancy within eBay.

eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at talent@ebay.com. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility.

We use cookies to enhance your experience and may use AI tools for administrative tasks in the hiring process. To learn how we handle your personal data and use AI responsibly, please visit our Talent Privacy Notice, Privacy Center and AI Hiring Guidelines.

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

Complete your application on ebay.wd5.myworkdayjobs.com. The employer’s form will show what is required.

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Source & posting history

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Pay
The base pay range for this position is expected in the range below: C$142,400 - C$190,100 Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience. The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or other benefits (including RRSP eligibility, various paid time off benefits, such as PTO and parental leave). Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
Location & working pattern

Toronto, Ontario, Canada

Working pattern and location restrictions need checking in the full posting.

Work authorization

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Status in our records
Active
First seen by us
Aug 13, 2026
Recorded sightings
173
Last seen by us
Oct 8, 2026

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