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Senior Machine Learning Engineer

Superlinked

Superlinked

Software Engineering
Budapest, Hungary
Posted on Tuesday, November 7, 2023

🗒️Summary

Work on the framework that implements and translates the python based elements into production-grade vector embedding & indexing machinery capable of running in-memory and connecting to different data sources and vector databases.

👀 Sneak peek into the work you’ll do

Vector Computer

You will actively participate in conversations about the future of the product concerning the creation, maintenance and improvement of vectorizers that embed varying type of data. You will act as a bridge between Senior Python Developers, Data Scientists and Researchers in creating a software product that achieves the vision while staying true to pragmatic engineering decisions.

ML Pipeline

You will propose and execute on turning product ideas to highly scalable machine learning solutions that expose a simplified interface having reasonable defaults to function well with most use-cases.

Big Data

You will work on the separation of the execution plan from the online execution and the implementation of an interpreter to translate the Superlinked library elements to scalable Spark code.

📝 Your experience

You have experience working with production systems that handle millions of datapoints in batch and preferably in near real-time setup.

You are proficient with Python and tools connected to the data ecosystem (Pytorch, Tensorflow, LLMs). You know how vector based representations work and you see the potential in creating a computation layer on top of vector embeddings.

You write production ready scalable applications in Spark and are not afraid to take a solution from idea to deployment adding value at each step of the process.

Your experience in big data allows you to be pragmatic with an eye towards leveraging emerging technologies as they grow.

For more information please use the link below

https://superlinked.notion.site/Work-at-Superlinked-541f2d74ce714c889a1c6dba6dd0dbf1?pvs=4