Machine Learning Engineer
775.724 kr (SEK)/yr
372,94 kr (SEK)/hr
35.606 kr (SEK)/yr
The average machine learning engineer gross salary in Vasteras, Sweden is 775.724 kr or an equivalent hourly rate of 373 kr. This is 1% higher (+7.677 kr) than the average machine learning engineer salary in Sweden. In addition, they earn an average bonus of 35.606 kr. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Vasteras, Sweden. An entry level machine learning engineer (1-3 years of experience) earns an average salary of 542.629 kr. On the other end, a senior level machine learning engineer (8+ years of experience) earns an average salary of 878.995 kr.
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866.862 kr (SEK)
12 %
Based on our compensation data, the estimated salary potential for Machine Learning Engineer will increase 12 % over 5 years.
This chart displays the highest level of education for:
Machine Learning Engineer, the majority at 100% with bachelors.
Typical Field of Study: Computer Programming, Specific Applications
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The cost of living in Vasteras, Sweden is 1% less than the average cost of living in Sweden. Cost of living is calculated based on accumulating the cost of food, transportation, health services, rent, utilities, taxes, and miscellaneous.
View Cost of Living PageVästerås (Swedish: [vɛstɛˈroːs] ) is a city in central Sweden on the shore of Lake Mälaren in the province of Västmanland, 100 kilometres (62 miles) west of Stockholm. The city had a population of 127,799 at the end of 2019, out of the municipal total of 158,653, over 100,000 more than the next largest of the 17 localities included in the Västerås Municipality. Västerås is the seat of Västerås Municipality, which is the capital of Västmanland County and an episcopal see.
Sourced from WikipediaERI's compensation data are based on salary surveys conducted and researched by ERI. Cost of labor data in the Assessor Series are based on actual housing sales data from commercially available sources, plus rental rates, gasoline prices, consumables, medical care premium costs, property taxes, effective income tax rates, etc.
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