Poshmark

Staff Engineer, Machine Learning at Poshmark (Chennai, India)

Poshmark· Chennai, India·

Role details

Work type
Onsite
Employment
Full-Time

Job description

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.

Staff Engineer Machine Learning

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.

Why work at Poshmark

  • Culture & Values: Core values include "Focus on People," "Lead with Love," and "Embrace Your Weirdness." The company emphasizes authenticity, inclusion, and connection—both within the team and with the community.
  • Work Policy: Hybrid workplace model (mix of remote and on-site, varying by team). Redwood City HQ is the primary hub, with offices in Chennai, Vancouver, and New York City. Many engineering and corporate roles are expected to work from the office on a regular basis.
  • Benefits: Comprehensive health & wellness, flexible PTO, parental/family leave, 401K plan, remote work support, learning & development programs, and fun company events. Personal style (or not) is encouraged.
  • Engineering Culture: Tech stack includes AWS, Java, Python, Kotlin, Ruby on Rails, Swift, Kubernetes, Terraform, and more. Teams work on ML, infrastructure, data engineering, and platform products. The company focuses on empowering engineers with autonomy and driving impact from day one.
  • Stability & Outlook: Backed by Naver, a large and stable tech conglomerate, Poshmark has a solid financial footing and is actively hiring in engineering, data, and product roles.
  • Employee Ratings: 4.0/5.0 on LinkedIn (417 reviews) — Work-Life Balance: 4.3, Compensation: 3.6, Culture: 4.3, Career: 3.8.

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