Toronto, Ontario, Canada
Open 3 months, first seen by us 93 days agoThe 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.Read the full posting
Develop and deploy AI and ML models into production
Build and scale large data pipelines and distributed systems for ML
Work with large structured and unstructured marketplace datasets
Partner with engineering, product, data and applied science to ship ML
Contribute to ML infrastructure, deployment, monitoring and operations
Develop and deploy state-of-the-art AI and ML models into production
Build and scale large data pipelines and distributed systems that support production ML applications
Work with large and unique datasets, including structured and unstructured marketplace data
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
Experience building large-scale distributed applications
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 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.
Open 3 monthsWe first saw this posting 93 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 93
Up longer than most. Similar jobs usually come down between day 8 and day 76.
Well past eBay’s usual: its jobs come down by about day 34.
From 5,517 similar postings that came down, and 69 of eBay’s. Coming down is not always a hire.
32 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- 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.
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New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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$190,100Base 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.
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Selected passages from the saved posting. Check the full description for conditions and exceptions.
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.
Toronto, Ontario, Canada
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.