This trainee role focuses on learning how digital maps are created and maintained using HERE’s spatial tools. Through guided, hands‑on practice, you will gradually build the ability to apply navigation attributes and understand map data structures.
During the training period, you will also gain exposure to basic data engineering tasks such as cleaning, deduplicating, and formatting datasets. As your knowledge grows, you may assist with AI and machine learning activities including data annotation and support for model training.
The position also provides opportunities to contribute to simple software tools and proof‑of‑concept applications that help improve internal processes and technical workflows.
This position is offered as a one‑year contract on the company payroll and does not guarantee a full‑time role after completion.
Main Responsibilities
Learn HERE Spatial Toolsets
- Participate in structured training and guided practice using HERE’s mapping tools.
- Apply navigation attributes such as names, addresses, speed categories, functional classes, intersections, and restricted maneuvers under supervision.
Develop Map Attribution Skills
- Work on real map features with mentor guidance to build domain knowledge.
- Improve mapping accuracy and consistency through practical experience.
Follow Database and Quality Standards
- Learn mapping specifications and quality requirements.
- Ensure tasks meet established standards with regular reviews.
Support Data Preparation
- Assist with dataset cleaning, deduplication, filtering, balancing, and formatting.
Assist with AI and Machine Learning Tasks
- After completing core training, support annotation and training data preparation.
- Contribute to basic model training workflows under supervision.
Support Software and Application Tasks
- Work alongside senior team members to help build or maintain simple internal tools.
- Assist with proof‑of‑concept applications used for automation or scaling initiatives.
Candidate Profile
- Bachelor’s degree in Computer Science, Information Technology, AI/DS, or a related discipline from a recognized university.
- Basic knowledge of programming languages such as Python, Java, or C.
- Familiarity with frameworks or libraries like React and Node.js.
- Understanding of databases such as MySQL, MongoDB, or PostgreSQL.
- Knowledge of data structures and algorithms.
- Exposure to machine learning, data science, or artificial intelligence concepts is preferred but not mandatory.