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Machine learning engineer

Sumaré
Dexian
Anunciada dia A 12 h atrás
Descrição

Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. Responsibilities Study and transform data science prototypes Design machine learning systems Research and implement appropriate ML algorithms and tools Develop machine learning applications according to requirements Select appropriate datasets and data representation methods Run machine learning tests and experiments Perform statistical analysis and fine-tuning using test results Train and retrain systems when necessary Extend existing ML libraries and frameworks Keep abreast of developments in the field Requirements Proven experience as a Machine Learning Engineer or similar role Understanding of data structures, data modeling and software architecture Deep knowledge of math, probability, statistics and algorithms Ability to write robust code in Python, Java and R Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn) Excellent communication skills Ability to work in a team Outstanding analytical and problem-solving skills BSc in Computer Science, Mathematics or similar field; Masters degree is a plus. Dexian is a leading provider of staffing, IT, and workforce solutions with over 12,000 employees and 70 locations worldwide. As one of the largest IT staffing companies and the 2nd largest minority-owned staffing company in the U.S., Dexian was formed in 2023 through the merger of DISYS and Signature Consultants. Combining the best elements of its core companies, Dexian's platform connects talent, technology, and organizations to produce game-changing results that help everyone achieve their ambitions and goals.Dexian's brands include Dexian DISYS, Dexian Signature Consultants, Dexian Government Solutions, Dexian Talent Development and Dexian IT Solutions. Visit https://dexian.com/ to learn more.Dexian is an Equal Opportunity Employer that recruits and hires qualified candidates without regard to race, religion, sex, sexual orientation, gender identity, age, national origin, ancestry, citizenship, disability, or veteran status.

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