Elevate the Quality of Geospatial Intelligence through Machine Learning

An innovative geospatial data initiative is enhancing the accuracy and intelligence of large-scale mapping systems. To support this work, we are seeking a versatile and technically skilled Machine Learning Engineer to build scalable ML models, apply advanced data science methods, and deploy robust solutions that improve data quality and insight.

This role offers a unique opportunity to shape the backbone of mapping technologies by working at the crossroads of software engineering, machine learning, and geospatial analytics. You will play a key role in identifying anomalies, improving feature extraction, and developing scalable models that support critical infrastructure.

About the Role

You will be responsible for the full ML lifecycle—design, development, deployment, and monitoring—of models used to analyse, enhance, and validate geospatial datasets. Your work will span natural language processing (NLP), outlier detection, data quality quantification, and deep learning to support data-intensive map systems.

Success in this role will require not just strong machine learning expertise, but also sound software engineering skills, with the ability to bring models into production at scale. You will work closely with other developers and data scientists to turn experimental solutions into stable services.

Main Responsibilities

• Develop, optimise, and maintain machine learning models that process and enhance large geospatial datasets
• Apply statistical methods and data science techniques to quantify data quality and extract meaningful insights
• Use outlier detection to identify anomalies and guide data improvement efforts
• Design NLP models and integrate them into automated systems for information extraction
• Collaborate on scalable infrastructure to support ML model deployment and continuous performance monitoring
• Own and deliver features and model improvements end to end, from concept to implementation

What We Are Looking For

Required qualifications:

• Extensive programming experience with Python, and either Scala or Java
• Proven expertise in machine learning and data science, including techniques such as classification, clustering, feature engineering, anomaly detection, and neural networks
• Deep understanding of classical algorithms including SVM, Random Forest, Naive Bayes, and KNN
• Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or Keras
• Strong familiarity with data science libraries such as Scikit-learn, Numpy, and Pandas
• Excellent analytical, problem-solving, and communication skills
• Ability to work independently and collaboratively in an agile setting

Preferred qualifications:

• Experience in Natural Language Processing, information retrieval, or data mining
• Background in statistical modeling and predictive analytics

What You Can Expect

• A high-impact role shaping the quality and intelligence of geospatial mapping systems
• A technically challenging environment that blends cutting-edge ML research with practical engineering
• Collaboration with a team dedicated to continuous improvement, data integrity, and operational excellence
• Full-time, on-site role based in Malmö, offering exposure to advanced data infrastructure and real-world applications
• A flexible project-based contract with competitive hourly rates

How to Apply

If you are an experienced machine learning engineer passionate about building systems that make data smarter and more useful, we encourage you to apply. We welcome candidates of all backgrounds and identities.

Please submit your CV by clicking on the Apply Button. Applications will be reviewed on a continuous basis. We will only contact you in the event of an interview invitation.