Machine Learning Engineer

Quick Facts

• Role: Machine Learning Engineer

• Work mode: Remote (Hybrid: 3 days/week in Malmö office)

• Location note: Commuting possible for the first 3 months; relocation to Sweden required afterwards

Description

You will build and deploy machine learning solutions to improve the quality, accuracy, and reliability of large-scale geospatial datasets. The work includes classical ML and NLP models to extract structured information, detect anomalies, and identify data quality issues, plus LLM-based prompt engineering and agent workflows. You’ll own features across the full ML lifecycle—from experimentation and model development to production deployment and large-scale rollout.

Responsibilities

• Design, develop, and deploy machine learning models

• Build and maintain scalable data and software solutions

• Apply data science techniques to analyze datasets and improve data quality

• Develop ML and NLP solutions for information extraction, anomaly detection, and data validation

• Work with LLMs, including prompt engineering and agent-based workflows

• Take ownership of improvements from experimentation through production deployment

• Collaborate with cross-functional teams to integrate ML models into production systems

Requirements

• Strong programming skills and extensive hands-on experience with Python

• Proven experience in Machine Learning and Data Science (classification, clustering, feature engineering, anomaly detection, neural networks)

• Practical experience working with LLMs (prompt engineering and agent-based workflows)

• Solid understanding of classical ML algorithms (SVM, Random Forest, Naive Bayes, k-NN)

• Experience with ML frameworks and libraries (PyTorch, TensorFlow, Keras, Scikit-learn, NumPy, Pandas)

• Strong analytical thinking and problem-solving skills

• Ability to balance innovative approaches with practical implementation in existing systems

• Excellent written and verbal communication skills

• Proactive, ownership-driven mindset and ability to adapt in a fast-paced environment

Benefits

• Opportunity to work on globally used web and developer platforms

• Direct impact on frontend architecture, APIs, and developer-facing solutions

• Collaboration with international, cross-functional engineering and product teams

• Work on large-scale mapping and location-based technologies used worldwide