JobgetherRemote · Canada
1h ago
PoshmarkPosted 3d ago
L4
Staff Engineer, Machine Learning
Staff Engineer, Machine Learning at Poshmark scores 90 out of 100 on AI centrality, which makes it a Level 4 role on this board.
Remote (IN Tamil Nadu (Chennai) - Office)seniorFullTime
AI in this role
Build and scale next-generation machine learning algorithms and big data platforms to improve user experience on Poshmark.
pytorchtensorflowkerasscalapythonmongodbredshiftdruidairflowjenkinssparksparkml+1
machine-learningbig-datadistributed-systemsalgorithms
About Poshmark
Poshmark is the leading fashion marketplace where style comes alive through discovery, self-expression, and human connection. Powered by a vibrant community of 165 million members, Poshmark brings real people and taste to shopping through a social experience shaped by shared discovery. Buying and selling fashion feels simple, joyful, and personal, while every item tells its own story. Poshmark empowers sellers to grow meaningful businesses, keeps fashion in circulation longer, and gives shoppers access to unique and trusted finds, from everyday pieces to one-of-a-kind vintage and luxury.
Big Data team is a central player in the Poshmark organization. Our mission is to build a world-class big data platform to bring value out of data for us and for our customers. Our goal is to democratize data, support exploding business, build data and ML pipelines to fuel existing and new business critical initiatives.
We are looking for exceptional, creative and passionate Machine Learning engineers to join our ML and Big Data Team. You will be responsible for building and owning the next-generation of algorithms and systems that would have critical business impact for Poshmark and improve the user experience for our millions of users
Responsibilities
Explore large datasets, research and develop algorithms/models to solve interesting business problems.
Design and code highly scalable, machine learning applications processing large volumes of data.
Collaborate with multiple teams - data science, business, engineering and help deliver Machine learning based Data products across the company.
Develop best practices and tools to enable robust delivery of features
Design and improve architecture in order to ensure horizontal scalability at all layers
Ideal Candidate
Strong background in Machine Learning with deep understanding of algorithms and modeling techniques
8+ years of overall software development experience with at least 5+ years of industry experience applying Machine Learning to concrete problems
Great coding skills and strong software development experience with Big Data technologies & Machine Learning frameworks like SparkML, TensorFlow, PyTorch, Keras
Understanding of distributed systems, and large scale engineering challenges is plus.
Technologies we use
Scala, Python
MongoDB, Redshift, Druid
Airflow, Jenkins
Spark, SparkML, Kinesis
Why Poshmark?
Poshmark is a leading social commerce platform for the next generation of retailers and shoppers. Through technology, our mission is to build the world’s most connected shopping experience, while empowering people to build thriving retail businesses.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Machine LearningBig DataDistributed SystemsAlgorithmsPyTorchTensorFlowKerasScala
Questions you could be asked
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where big data was part of your work. What did you do?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where algorithms was part of your work. What did you do?
- Walk me through how you've used PyTorch in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Machine Learning, Big Data, Distributed Systems, Algorithms, and PyTorch. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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