ML Engineer Machine Learning & Geospatial Data - 20093
Veritaz AB · Malmö · 6 månader – upp till 12 månader · Deadline 2026-11-14
Veritaz is recruiting an **ML Engineer** to design, develop, test, and deploy machine learning systems that improve the quality of large-scale geospatial datasets. Working across the **full development lifecycle**, the position involves building classical machine learning and natural language processing models to extract structured information, detect anomalies, and measure data quality. Key responsibilities include creating and maintaining scalable data pipelines, working with large language models and agent-based workflows, developing algorithms for classification and clustering, and integrating finished solutions into production systems alongside cross-functional teams. Candidates must have strong **Python programming** abilities, proven experience in machine learning and data science, and practical software engineering skills. Essential qualifications include a solid foundation in classical machine learning algorithms such as SVM, Random Forest, Naive Bayes, and k-NN, alongside hands-on proficiency with tools including PyTorch, TensorFlow, Keras, Scikit-learn, NumPy, and Pandas. Experience with LLMs, prompting techniques, and agent-based workflows is also required, coupled with strong analytical problem-solving and communication skills. Additional experience with Scala or Java, statistical modelling, predictive model development, or specialized knowledge in NLP, information retrieval, and data mining is considered meritorious.
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.
Job Overview
Assignment Description
We are looking for an ML Engineer to develop and deploy machine learning systems that improve the quality of large-scale geospatial datasets. You will build classical machine learning and NLP models to extract structured information, detect anomalies, and measure data quality.
The role covers the full development lifecycle, from experimentation and model development to production integration and deployment at scale. Strong Python programming, data science expertise, and software engineering skills are essential.
What You Will Work On
- Design, develop, test, and deploy machine learning models.
- Build and maintain scalable data pipelines and software solutions.
- Apply data science techniques to improve data quality and generate insights.
- Work with LLMs, prompting techniques, and agent-based workflows.
- Develop models for classification, clustering, feature engineering, and anomaly detection.
- Integrate ML models into production systems.
- Own features and improvements from development through delivery.
- Collaborate with cross-functional teams to deliver reliable solutions.
What You Bring
- Strong Python programming skills.
- Proven experience in machine learning and data science.
- Solid understanding of classical ML algorithms, including SVM, Random Forest, Naive Bayes, and k-NN.
- Experience with LLMs, prompting, and agent-based workflows.
- Hands-on experience with PyTorch, TensorFlow, Keras, Scikit-learn, NumPy, and Pandas.
- Strong analytical thinking and problem-solving skills.
- Ability to balance innovative approaches with practical software delivery.
- Excellent written and verbal communication skills.
- A proactive mindset, strong ownership, and the ability to work in a fast-paced environment.
Meritorious
- Experience with Scala or Java.
- Knowledge of NLP, information retrieval, or data mining.
- Experience in statistical modelling and predictive model development.