Staff Applied AI Scientist
About The Position
At Poshmark, we're passionate about harnessing the power of data to drive business impact. As an Applied AI Scientist, you'll tackle complex challenges in personalization, trust & safety, marketing optimization, and product experience. With over 130 million users generating billions of daily events, you'll be at the forefront of data science innovation, developing AI solutions that enhance our platform and delight our community. Lead end-to-end data science initiatives, from ideation to deployment, delivering measurable business impact through projects such as feed personalization, product recommendation systems, computer vision and GenAI. Collaborate cross-functionally with ML engineers, product managers, and business stakeholders, to design and deploy high-impact models. Develop scalable solutions for key areas of product, marketing, operations, and community functions. Own the entire ML development lifecycle: data exploration, model development, deployment, and performance optimization. Explore and experiment with emerging AI trends, technologies, and methodologies to keep Poshmark at the cutting edge. 6-Month Accomplishments: Develop comprehensive understanding of Poshmark's data platform and key datasets. Gained insights into challenges related to data scale and noise, implementing strategies to effectively leverage data in decision-making processes. Demonstrated proficiency in Poshmark's machine learning systems by applying advanced algorithms to address a business use case. Successfully prototype/enhance models aimed at improving key business metrics, contributing to data-driven solutions that support company objectives 12+ Month Accomplishments: Collaborated with ML engineers and other data scientists to establish best practices for managing and maintaining machine learning models in production, enhancing system reliability. Successfully led the development and deployment of model for resolving business use case(s), contributing to overall company growth and success Lead the adoption and application of cutting-edge AI trends and technologies, establishing Poshmark as a pioneer in data science. Mentor junior scientists/engineers, fostering a culture of continuous learning and development within the team.
Requirements
- 5–8 years of experience building scalable data science solutions in a big data environment.
- Hands-on experience with key machine learning algorithms, including CNNs, Transformers, and Vision Transformers.
- Proficiency in Python, SQL, and Spark (Scala or PySpark), with experience in deep learning frameworks such as PyTorch or TensorFlow.
- Solid understanding of linear algebra, statistics, probability, calculus, and A/B testing concepts.
- Strong problem-solving skills and the ability to communicate complex technical ideas effectively to diverse audiences, including executives and engineers.
Nice To Haves
- Experience with personalization algorithms, recommendation systems, or user behavior modeling.
- Familiarity with Large Language Models (LLMs) and techniques such as Retrieval-Augmented Generation (RAG) or Parameter-Efficient Fine-Tuning (PEFT).
Responsibilities
- Lead end-to-end data science initiatives, from ideation to deployment, delivering measurable business impact through projects such as feed personalization, product recommendation systems, computer vision and GenAI.
- Collaborate cross-functionally with ML engineers, product managers, and business stakeholders, to design and deploy high-impact models.
- Develop scalable solutions for key areas of product, marketing, operations, and community functions.
- Own the entire ML development lifecycle: data exploration, model development, deployment, and performance optimization.
- Explore and experiment with emerging AI trends, technologies, and methodologies to keep Poshmark at the cutting edge.
- Mentor junior scientists/engineers, fostering a culture of continuous learning and development within the team.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
