Poshmark
www.poshmark.comAbout
The Story
Founded in 2011, Poshmark started with a simple yet powerful idea in Manish Chandra's garage. Along with co-founders Tracy Sun, Gautam Golwala, and Chetan Pungaliya, Chandra envisioned a platform that would revolutionize how people buy and sell fashion. The inspiration came from seeing the potential of the iPhone 4 to create meaningful connections in the shopping experience.
What They Do
Poshmark is not just another e-commerce platform – it's a social marketplace that brings together shopping and community. Think of it as a place where social media meets shopping, allowing users to buy, sell, and discover fashion, home goods, and accessories. With over 80 million users , the platform has become a go-to destination for both casual sellers and entrepreneurial individuals looking to build their own digital boutiques.
Growth & Achievements
- Started as a fashion-only platform and successfully expanded into home goods and electronics
- Raised over $160 million in venture funding
- Achieved a successful IPO in January 2021
- Recently launched innovative features like AI-powered visual search and livestream shopping
- Built a vibrant community of millions of buyers and sellers across the country
Today, under CEO Manish Chandra's leadership, Poshmark continues to innovate in the social commerce space, blending technology with community to create a unique shopping experience. The platform's success story is a testament to how combining social connections with commerce can create a powerful marketplace that resonates with modern consumers.
Candid answers by the company
Poshmark is a social commerce marketplace where people buy and sell fashion, home goods, and accessories. The platform combines social media features with e-commerce, allowing users to create digital boutiques while engaging in an interactive, community-driven shopping experience.
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Jobs at Poshmark
Machine Learning (ML)
PythonAre you passionate about the power of data and excited to leverage cutting-edge AI/ML to drive business impact? At Poshmark, we tackle complex challenges in personalization, trust & safety, marketing optimization, product experience, and more.
Why Poshmark?
As a leader in Social Commerce, Poshmark offers an unparalleled opportunity to work with extensive multi-platform social and commerce data. With over 130 million users generating billions of daily events and petabytes of rapidly growing data, you’ll be at the forefront of data science innovation. If building impactful, data-driven AI solutions for millions excites you, this is your place.
What You’ll Do
- Drive end-to-end data science initiatives, from ideation to deployment, delivering measurable business impact through projects such as feed personalization, product recommendation systems, and attribute extraction using computer vision.
- Collaborate with cross-functional teams, including ML engineers, product managers, and business stakeholders, to design and deploy high-impact models.
- Develop scalable solutions for key areas like product, marketing, operations, and community functions.
- Own the entire ML Development lifecycle: data exploration, model development, deployment, and performance optimization.
- Apply best practices for managing and maintaining machine learning models in production environments.
- Explore and experiment with emerging AI trends, technologies, and methodologies to keep Poshmark at the cutting edge.
Your Experience & Skills
- Ideal Experience: 6-9 years of building scalable data science solutions in a big data environment. Experience with personalization algorithms, recommendation systems, or user behavior modeling is a big plus.
- Machine Learning Knowledge: Hands-on experience with key ML algorithms, including CNNs, Transformers, and Vision Transformers. Familiarity with Large Language Models (LLMs) and techniques like RAG or PEFT is a bonus.
- Technical Expertise: Proficiency in Python, SQL, and Spark (Scala or PySpark), with hands-on experience in deep learning frameworks like PyTorch or TensorFlow. Familiarity with ML engineering tools like Flask, Docker, and MLOps practices.
- Mathematical Foundations: Solid grasp of linear algebra, statistics, probability, calculus, and A/B testing concepts.
- Collaboration & Communication: Strong problem-solving skills and ability to communicate complex technical ideas to diverse audiences, including executives and engineers.
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