7 of 7 MLlib Jobs in Scotland

or related language. Experience with neural deep learning methods and machine learning. PREFERRED QUALIFICATIONS Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, etc. Experience with large scale distributed systems such as Hadoop, Spark, etc. Our inclusive culture empowers Amazonians to deliver the best More ❯

Experience working with real-world data sets and building scalable models from big data Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow Experience with large scale distributed systems Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a More ❯

deep learning methods and machine learning - Experience with prompting techniques for LLMs PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - PhD in math/statistics/engineering or other More ❯

or related language - Experience with neural deep learning methods and machine learning PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. Our inclusive culture empowers Amazonians to deliver the best More ❯

CS, Machine Learning, Operations Research or in a highly quantitative field. - Knowledge of distributed computing and experience with advanced machine learning libraries like Spark MLLib, Tensorflow, MxNet, etc. - Strong publication record in international conferences on machine learning and artificial intelligence Our inclusive culture empowers Amazonians to deliver the best results More ❯

techniques and concepts sampling methods, Regression Properties of distributions Weighting sample-based data Statistical tests proper usage Real-world applications. Python - NumPy, SciPy, Pandas, MLlib, scikit-learn, and other common data and machine learning related libraries Working knowledge of SQL, data structures and databases (Snowflake - desirable) This is a pragmatic More ❯

techniques and concepts sampling methods, Regression Properties of distributions Weighting sample-based data Statistical tests proper usage Real-world applications. Python - NumPy, SciPy, Pandas, MLlib, scikit-learn, and other common data and machine learning related libraries Working knowledge of SQL, data structures and databases (Snowflake - desirable) This is a pragmatic More ❯