MLlib Jobs in Scotland

5 of 5 MLlib Jobs in Scotland

Sr. Applied Scientist, Campaign and Creative

Edinburgh, United Kingdom
Amazon
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 ❯
Employment Type: Permanent
Salary: GBP Annual
Posted:

Sr. Applied Scientist, Trustworthy Shopping Experience (TSE) Ops Product team

Edinburgh, United Kingdom
Amazon
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 ❯
Employment Type: Permanent
Salary: GBP Annual
Posted:

Applied Science Manager, Traffic Quality ML

Edinburgh, Scotland, United Kingdom
Amazon
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 ❯
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Data Scientist

Glasgow, Scotland, United Kingdom
Okta Resourcing
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 ❯
Posted:

Data Scientist

Edinburgh, Scotland, United Kingdom
Okta Resourcing
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 ❯
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