Experienced ML Python Engineer
- Netanya, Israel
Outbrain's AutoML team is looking for an Experienced ML Python Engineer. The AutoML team is part of Outbrain’s Recommendations Group - about 40 machine learners, data scientists, and backend engineers who are responsible for everything that Outbrain recommends in its feeds and widgets. The team uses an interplay of Python, Java, and Rust, in addition to Spark, BigQuery, and Tensorflow to form our ML pipelines.
AutoML team’s responsibilities:
We are developing a suite of state-of-the-art Machine-Learning tools which are used by Outbrain's data scientists. We work closely with the research group to build Outbrain’s Machine Learning infrastructure.
Our team is integrating Outbrain’s big data capabilities, Machine Learning algorithms, and production development into components that are used for both research and production.
Your personal responsibilities are:
- Collaborate with data scientists and backend engineers to research, develop, and deploy machine learning models at a large scale
- Leverage Outbrain's rich data sources and large-scale computing resources to build systems that process terabytes of data to improve outcomes for our publishers and advertisers
- Perform software research, development, evaluation, and optimization
Who you are:
- BSc\MSc\PhD in Computer Science, Statistics, Software, Information Systems Engineering or similar or equivalent industry experience
- Python backend engineer - at least 3 years of proven industry experience with Machine Learning algorithms and data engineering
- Experience working with large-scale data-intensive systems and big data technologies (Hadoop, Hive, Spark, etc.)
- Java/Scala backend experience - an advantage.
- Multidisciplinary and independent
- Great communication and interpersonal skills
What we offer:
- Competitive salary and great work/life balance.
- Working fully remotely due to COVID in the foreseeable future.
- Making a business and technical impact in a global company. The company is global, but at the same time small enough that a single person in this position can have a significant and measurable impact
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