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DP Group

AI/Data Engineer Intern

Posted 3 Hours Ago
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In-Office
Singapore, SGP
Internship
In-Office
Singapore, SGP
Internship
Assist in building and maintaining data ingestion pipelines and storage for AI workflows. Implement deployment, security, and monitoring for applications; collaborate with stakeholders and design teams; test and validate data verification and AI workflows; document solutions and follow best practices while continuously learning new tools.
The summary above was generated by AI

COMPANY:

Spatial Intelligence For Design Pte Ltd

BUILD YOUR FUTURE WITH US

Every DPian Matters is the motto that reflects our core values. DP Architects actively supports the growth of our people through dedicated talent development programmes, clear career pathways and access to global opportunities. Our culture of continuous learning, collaboration and shared purpose develops skilled and engaged people deeply invested in the future of our built environment. Our practice is defined by the pursuit of design excellence, supported by research and innovation, and anchored in teamwork for the collective good. Together, we pursue better-than-sustainable outcomes to shape a regenerative future for our cities and communities.

JOB SUMMARY:
A hands-on AI/Data Engineering Intern to support our data pipeline and preparation work. You will be working closely with our AI Engineer to design data ingestion pipelines and storage procedures to ensure our data is clean, structured, and ready for use in AI workflows. You will also design algorithms for the actual AI workflows.
JOB RESPONSIBILITIES:
Data pipeline development:

  • Analyse and provide potential solutions for eliminating uncertainty in identifying objects in construction data;

  • Integrate pipeline with existing applications;

Deployment, Security and Maintenance:

  • Deploy digital solutions to various environments, ensuring scalability, security, and reliability;

  • Implement security measures for applications, such as securing APIs, managing authentication and authorization mechanisms, and ensuring data integrity;

  • Monitor, maintain, and improve the performance of deployed applications, including bug-fixing;

Technical Collaboration:

  • When needed, work with stakeholders to understand requirements and technical specifications to deliver functional solutions;

  • Collaborate with designers, architects, and other team members to ensure solutions meet user needs and project goals;

Testing and Quality Assurance:

  • Use test harnesses to test hypotheses and continuously validate efficacy of data verification pipeline and downstream AI workflows;

  • Participate in code reviews and contribute to the establishment of best practices;

Documentation:

  • Prepare and maintain clear documentation for developed solutions, including APIs, workflows, and deployment guidelines;

  • undefined

Continuous Learning: 

  • Stay updated with the latest technologies, frameworks, and tools to contribute innovative ideas to the team;

JOB REQUIREMENTS:
Bachelor’s degree in Computer Science, Software Engineering, or a related field;

  • Technical Skills:

    • Experience in:

      • Data analysis technologies:

        • Python;

        • pandas;

        • matplotlib;

      • Database technologies: Postgres, MongoDB;

      • Deployment technologies: Docker;

      • Version control: Git;

  • Problem-Solving Skills: Strong analytical and problem-solving skills with attention to detail;

  • Team Collaboration: Ability to work effectively in a team environment, communicate ideas clearly, and contribute to project success;

  • Learning Attitude: Willingness to learn and adapt to new technologies and frameworks;

GOOD TO HAVE:

  • Familiarity with machine learning methodologies and technologies such as Pytorch or TensorFlow;

  • Familiarity with graphics processing algorithms;

  • Familiarity with software development for AEC (Architecture, Engineering, and Construction) tools like Revit, Rhino, or Sketchup;

  • Knowledge of API design and development;

  • Exposure to CI/CD pipelines for software deployment;

  • Understanding of Agile methodologies and project management tools ([e.g., Jira, Trello, Kanban]);

  • A portfolio or GitHub repository showcasing past projects or code samples.

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