
Machine Learning Engineer, NLP
We’re looking for an experienced Machine Learning Engineer with a natural language processing (NLP) background to join our team at Snapchat. We’re searching for a creative problem-solver who is passionate about working on cutting-edge technologies that will shape the future of mobile communication.The ideal candidate has a strong technical background in machine learning, NLP, and deep learning. They should be comfortable with prototyping and testing, and be able to quickly iterate and optimize their algorithms. They should have a keen interest in staying up-to-date with the latest technologies and understand their implications for our industry. They should also be a great collaborator who enjoys working with a diverse team of engineers, designers, and business partners.If you’re excited about making an impact in the mobile communication space and have the qualifications we’re looking for, we want to hear from you!
Proficiency In Programming Languages Such As Python
Strong Knowledge Of Machine Learning Algorithms
Such As Knn
Lstm
And Cnn
Expertise In Natural Language Processing (Nlp) Techniques
Such As Tokenization
Stemming
And Lemmatization
Java And C++
Knowledge Of Big Data Technologies Such As Hadoop
Spark And Hive
Familiarity With Deep Learning Frameworks Such As Tensorflow And Keras
Python
Data Analysis
Machine Learning
Deep Learning
Scikit-learn
Tensorflow
Data Visualization
Algorithm design
Model training
Natural language processing
Data Mining
Data engineering
NLP
Neural Networks
AI
Communication
Conflict Resolution
Leadership
Problem Solving
Time management
Interpersonal Skills
creativity
Organization
Teamwork
Adaptability
According to JobzMall, the average salary range for a Machine Learning Engineer, NLP in Los Angeles, CA, USA is $103,842 to $163,719. The median salary for this position is $133,781.
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Snapchat is a multimedia messaging app developed by Snap Inc., originally Snapchat Inc. One of the principal features of Snapchat is that pictures and messages are usually only available for a short time before they become inaccessible to their recipients.

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