Job Description
This role is designed to help a trainee learn how digital maps are created and maintained using HERE’s specialized spatial tools. You’ll gradually build skills in applying navigation attributes and understanding map data through guided, hands‑on practice.
Along the way, you will be introduced to basic data‑engineering tasks such as cleaning, deduplication, and formatting datasets. As your map knowledge develops, you will also support AI/ML activities, including data annotation and model‑training assistance. Additionally, you will have opportunities to contribute to simple software tools and proof‑of‑concept applications that help improve internal processes and technical workflows.
This is a one-year contract on company payroll and does not guarantee a full-time opportunity after the contract ends.
MAIN RESPONSIBILITIES (Apprentice/Trainee Version)
Learn to use HERE’s Spatial Toolsets:
- Receive structured training and guided practice to apply basic navigation attributes—such as names, addresses, speed categories, functional classes, intersections, and restricted maneuvers—under close supervision.
Develop Map Attribution Skills:
- Build domain knowledge through hands‑on, mentor‑supported work on real map features, gradually improving accuracy and consistency.
Follow Database & Quality Standards:
- Learn the required mapping specifications and quality expectations, with your work reviewed regularly to ensure understanding and compliance.
Support Data Preparation Tasks:
- Assist with data cleaning, deduplication, filtering, balancing, and formatting while being trained on foundational data‑engineering concepts.
Contribute to AI/ML Activities (After Core Training):
- Once you have enough map knowledge, you will be introduced to annotation tasks, training‑data preparation, and basic model‑training workflows—all with supervision.
Assist in Basic Software/Application Support:
- Work with senior team members to help build or maintain simple tools or proof‑of‑concept applications used for automation or scale‑up initiatives
Who are you?
- Educational Background: A degree – Bachelor of Science in Computer Science, Information Technology, AI/DS or a related field from a reputed universityBasic knowledge in any of the Programming language (viz. Python, Java, C), Libraries/framework (viz. React.JS, Node.js), database (viz, MySQL, MongoDB, PostgreSQL), Developer tools (MySQL, MongoDB, PostgreSQL) and Data Structures and Algorithm
- Basic knowledge & understanding or certification training in Machine Learning, Data Science and Artificial Learning concepts would be preferred, but not mandatory
- Fast learner: An eye for detail, strong problem-solving and debugging skills
- Technical Aptitude: Strong interest in IT applications and systems
- Communication Skills: Good verbal and written communication skills
- Problem-Solving Skills: Ability to analyze problems and find solutions
- Adaptability: Willingness to learn new technologies
