IN Draft

Poshmark; Chennai District; In loco; INR 4.200.000 - 7.000.000; Tempo pieno

Descrizione del lavoro

Poshmark is seeking a Staff Engineer with Machine Learning to join our Big Data team in building a world-class data platform. You will own algorithms and systems impacting millions of users, and collaborate with data science, business, and engineering teams to deliver scalable ML-based data products.

You should have deep ML expertise, strong software development background, and experience with large-scale data processing and ML frameworks.

Competenze

• 8+ years of overall software development experience with at least 5+ years applying Machine Learning to concrete problems.
• Strong background in Machine Learning with deep understanding of algorithms and modeling techniques.
• Experience with distributed data processing and large-scale ML systems is highly desirable.

Mansioni

• Explore large datasets, research and develop algorithms/models to solve business problems.
• Design and code scalable ML applications processing large volumes of data.
• Collaborate with data science, business, and engineering teams to deliver ML-based data products.

Conoscenze

Machine Learning

Big Data

Distributed Systems

Scala

Python

Strumenti

SparkML

TensorFlow

PyTorch

Keras

Airflow

Jenkins

MongoDB

Redshift

Druid

Spark

Kinesis

Descrizione del lavoro

About Poshmark

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.