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Data/IT

Sista ansökningsdag 2026-07-02

AI Engineer 18008

Veritaz ABTidsbegränsad anställningPublicerad 2026-06-02

Veritaz is a leading IT staffing solutions provider in Sweden, committed to advancing individual careers and aiding employers in ensuring the perfect talent fit. With a proven track record of successful partnerships with top companies, we have rapidly grown our presence in the USA, Europe, and Sweden as a dependable and trusted resource within the IT industry. Assignment Description We are currently looking for an experienced Machine Learning Engineer What You Will Work On Design, develop, and deploy machine learning models for large-scale data processing Build and maintain scalable software and data solutions Develop machine learning systems that improve data quality and data reliability Apply data science techniques to generate insights from large geospatial datasets Develop classification, clustering, anomaly detection, and predictive models Design and implement NLP solutions for structured information extraction Work with Large Language Models (LLMs), prompting strategies, and agent-based workflows Develop feature engineering pipelines and model evaluation frameworks Support model integration, productionization, and deployment activities Collaborate with software engineers, data engineers, and business stakeholders Optimize model performance, scalability, and operational efficiency Own features and technical deliverables throughout the entire development lifecycle Support continuous improvement of AI and machine learning capabilities What You Bring Strong programming skills with extensive experience in Python Proven experience developing machine learning and data science solutions Hands-on experience with classification, clustering, feature engineering, anomaly detection, and neural networks Experience working with Large Language Models (LLMs) Knowledge of prompt engineering and agent-based AI workflows Strong understanding of classical machine learning algorithms including: Support Vector Machines (SVM) Random Forest Naive Bayes k-Nearest Neighbors (k-NN) Exp

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