Confidence can sometimes hold us back from applying for a job. Here's a secret: there's no such thing as a "perfect" candidate. Poshmark is looking for exceptional people who want to make a positive impact through their work and help create an organization where everyone can thrive. So whatever background you bring with you, please apply if this role would make you excited to come to work every day.
Job Description:Our AI / Machine Learning team is a central player in the Poshmark organization. Our mission is to build a world-class machine learning platform to bring value out of data for us and for our customers. Our goal is to democratize data science and machine learning, support exploding business, and use machine learning to drive value across the chain (Search, personalization, fraud detection, catalog digitization to name a few).
The Machine Learning Engineering team at Poshmark is looking for an experienced machine learning engineer to take care of Poshmark's requirement to take machine learning models with varying requirements to production ..
Responsibilities:- Build tools and infrastructure to democratize ML
- Productionizing ML models in collaboration with the Data Science and other Engineering teams.
- Maintain and support existing platforms and evolve to newer technology stacks and architectures.
Desired Skills & Experience:- 2-3 years of relevant software engineering experience with data intensive applications
- Good understanding of data science concepts and machine learning lifecycle
- Good understanding of spark and sql and prior experience with writing backend apis
- Flexible and open to trying out newer technologies and adopting them as and when needed.
Technologies we use:- Flask, Docker, Kubernetes
- Redis, Redshift, MongoDB, Kafka, RabbitMQ, Kinesis
- sklearn, pyTorch, Tensorflow, Spark
- Mlflow, Sagemaker, Kibana, Airflow
Salary Range:$130,628.00 - $186,111.00 Annual
Poshmark is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
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