Asks for

The ad says“Strong CS fundamentals. Should be able to write algorithms with ease.”
The ad says“Good understanding of system architecture. Have knowledge of big data technologies – streaming architecture, data pipelines, etc.”
The ad says“Solid understanding of Data Science and ML fundamentals – Regression, Classification, Tree-based approach, Neural network, and sequence-based models.”
The ad says“Bachelors or Masters in Computer Science, Statistics, or related field”
The ad says“Good understanding of system architecture. Have knowledge of big data technologies – streaming architecture, data pipelines, etc.”
The ad says“Working experience with at least one ML model: LLMs, GNN, Deep Learning, Logistic Regression, Gradient Boosting trees, etc.”
The ad says“Working experience with at least one ML model: LLMs, GNN, Deep Learning, Logistic Regression, Gradient Boosting trees, etc.”
The ad says“Working experience with at least one ML model: LLMs, GNN, Deep Learning, Logistic Regression, Gradient Boosting trees, etc.”
The ad says“Experience with Python, SQL, Java or Scala”
The ad says“Working experience with at least one ML model: LLMs, GNN, Deep Learning, Logistic Regression, Gradient Boosting trees, etc.”
The ad says“Working experience with at least one ML model: LLMs, GNN, Deep Learning, Logistic Regression, Gradient Boosting trees, etc.”
The ad says“4+ years of experience applying Machine Learning to concrete problems at large scale”
The ad says“Solid understanding of Data Science and ML fundamentals – Regression, Classification, Tree-based approach, Neural network, and sequence-based models.”
The ad says“Experience with Python, SQL, Java or Scala”
The ad says“Solid understanding of Data Science and ML fundamentals – Regression, Classification, Tree-based approach, Neural network, and sequence-based models.”
The ad says“Experience with Python, SQL, Java or Scala”
The ad says“Solid understanding of Data Science and ML fundamentals – Regression, Classification, Tree-based approach, Neural network, and sequence-based models.”
The ad says“Experience with Python, SQL, Java or Scala”
The ad says“Good understanding of system architecture. Have knowledge of big data technologies – streaming architecture, data pipelines, etc.”
The ad says“Good understanding of system architecture. Have knowledge of big data technologies – streaming architecture, data pipelines, etc.”
The ad says“Solid understanding of Data Science and ML fundamentals – Regression, Classification, Tree-based approach, Neural network, and sequence-based models.”

Values

The ad says“Big data systems – Spark, EMR, S3, AirFlow”
The ad says“MLFlow, Sagemaker, Kibana, Airflow, Databricks, Grafana, Datadog”
The ad says“MLFlow, Sagemaker, Kibana, Airflow, Databricks, Grafana, Datadog”
The ad says“Docker, Kubernetes, Jenkins”
The ad says“Experience with Flask, FastAPI, RabbitMQ, Embeddings and Vector DBs”
The ad says“Big data systems – Spark, EMR, S3, AirFlow”
The ad says“Experience with Flask, FastAPI, RabbitMQ, Embeddings and Vector DBs”
The ad says“Experience with Flask, FastAPI, RabbitMQ, Embeddings and Vector DBs”
The ad says“MLFlow, Sagemaker, Kibana, Airflow, Databricks, Grafana, Datadog”
The ad says“Flask, Fastapi, Gunicorn, Quarkus”
The ad says“Docker, Kubernetes, Jenkins”
The ad says“Redis, Redshift, MongoDB, Spark, Kafka, RabbitMQ, Milvus”
The ad says“MLFlow, Sagemaker, Kibana, Airflow, Databricks, Grafana, Datadog”
The ad says“Docker, Kubernetes, Jenkins”
The ad says“Redis, Redshift, MongoDB, Spark, Kafka, RabbitMQ, Milvus”
The ad says“MLFlow, Sagemaker, Kibana, Airflow, Databricks, Grafana, Datadog”
The ad says“Redis, Redshift, MongoDB, Spark, Kafka, RabbitMQ, Milvus”
The ad says“Production experience with LLMs and prompt engineering”
The ad says“Pytorch, Tensorflow, Sklearn”
The ad says“Flask, Fastapi, Gunicorn, Quarkus”
The ad says“Experience with Flask, FastAPI, RabbitMQ, Embeddings and Vector DBs”
The ad says“Redis, Redshift, MongoDB, Spark, Kafka, RabbitMQ, Milvus”
The ad says“Redis, Redshift, MongoDB, Spark, Kafka, RabbitMQ, Milvus”
The ad says“Big data systems – Spark, EMR, S3, AirFlow”
The ad says“MLFlow, Sagemaker, Kibana, Airflow, Databricks, Grafana, Datadog”
The ad says“Pytorch, Tensorflow, Sklearn”
The ad says“Big data systems – Spark, EMR, S3, AirFlow”
The ad says“Pytorch, Tensorflow, Sklearn”
The ad says“Experience with Flask, FastAPI, RabbitMQ, Embeddings and Vector DBs”

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.

Senior Machine Learning Engineer

Poshmark is a leading social marketplace for new and secondhand styles for women, men, kids, home, and more. By combining the human connection of physical shopping with the scale, ease, and selection benefits of ecommerce, Poshmark makes buying and selling simple, social, and fun.

The 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 digitisation to name a few)

Responsibilities

Manage the entire ML lifecycle from data collection to deployment and monitoring
Collaborate across teams such as DS, QA, Infra and other engineering teams to productionize ML models
Write and optimize code for production environments, ensuring the robustness and reliability of ML services at scale
Manage and support current solutions while evolving them to incorporate newer technologies
Strong written, verbal, and presentation skills, with the ability to convey complex concepts in a clear and simple manner
Stay updated with the latest developments in data science and machine learning

Desired Skills & Experience

4+ years of experience applying Machine Learning to concrete problems at large scale
Bachelors or Masters in Computer Science, Statistics, or related field
Strong CS fundamentals. Should be able to write algorithms with ease.
Solid understanding of Data Science and ML fundamentals – Regression, Classification, Tree-based approach, Neural network, and sequence-based models.
Working experience with at least one ML model: LLMs, GNN, Deep Learning, Logistic Regression, Gradient Boosting trees, etc.
Should have excellent understanding of ML lifecycle
Good understanding of system architecture. Have knowledge of big data technologies – streaming architecture, data pipelines, etc.
Experience with Python, SQL, Java or Scala
Good to have:
- Big data systems – Spark, EMR, S3, AirFlow
- Production experience with LLMs and prompt engineering
- Experience with Flask, FastAPI, RabbitMQ, Embeddings and Vector DBs

Our Techstack

Pytorch, Tensorflow, Sklearn
Flask, Fastapi, Gunicorn, Quarkus
MLFlow, Sagemaker, Kibana, Airflow, Databricks, Grafana, Datadog
Docker, Kubernetes, Jenkins
Redis, Redshift, MongoDB, Spark, Kafka, RabbitMQ, Milvus

Why Poshmark?

Poshmark is a leading social marketplace for new and secondhand style for women, men, kids, pets, home, and more. By combining the human connection of physical shopping with the scale, ease, and selection benefits of ecommerce, Poshmark makes buying and selling simple, social, and sustainable. Its community of more than 70 million registered users across the U.S., Canada, and Australia is driving the future of commerce while promoting more sustainable consumption. For more information, please visit www.poshmark.com, and for company news and announcements, please visit investors.poshmark.com. You can also find Poshmark on Instagram, Facebook, Twitter, Pinterest, and YouTube.

About Us

At Poshmark, we’re constantly challenging the status quo and are looking for innovative and passionate people to help shape the future of Poshmark. We’re disrupting the industry by combining social connections with e-commerce through data-driven solutions and the latest technology to optimize our platform. We’re nothing without our amazing team who deliver an unparalleled social shopping experience to the millions of people we connect each day.

We built Poshmark around four core values:

Focus on People to create empowered communities that drive success;
Together we Grow to support each other to strive for our dreams;
Lead with Love to foster genuine connections built upon a foundation of respect; and
Embrace your Weirdness to accept and empower one another on their own unique journey.

We’re invested in our team and community, working together to build an entirely new way to shop. That way, when we win, we all win together. Come help us build the most connected shopping experience ever.