Job Description
We are looking for young, curious, and driven talents to join us in the exciting world of innovation at GAVATAR Siemens.
We are now building a complete Autonomous Building ecosystem that observes telemetry from global sites, analyzes KPIs using AI/ML models, and acts on real-time systems to improve energy efficiency, occupancy optimization, and operational performance.
At GAVATAR, you will work with global experts, experiment with cutting-edge technologies, and contribute to solutions that reduce carbon footprint, improve operational excellence, and enhance human digital experience. We encourage curiosity, ownership, diverse thinking, and bold ideas. Innovation is not just supported here — it is expected.
If you want to shape the digital future of real estate, work at the intersection of AI, sustainability, and smart infrastructure, and create impact on global scale — this is your opportunity.
Programming / Technical Skills:
- Solid proficiency in Python with a strong understanding of Object-Oriented Programming principles.
- Strong working knowledge of SQL and relational database concepts.
- Practical experience building RESTful APIs using Node.js.
- Hands-on exposure to React.js for building or integrating UI/dashboard components.
- Working knowledge of AWS services (Lambda, EC2, S3) and cloud deployment fundamentals.
- Foundational understanding of AI/ML concepts such as forecasting and anomaly detection.
- Exposure to Generative AI concepts with experience implementing Proof of Concepts (PoCs).
- Working understanding data integration and consumption from enterprise data platforms (e.g., Snowflake).
Team player:
The applicant must have good communication skills and be able to work collaboratively in a team environment.
Ability to translate business use-cases into technical architecture and scalable implementations.
Flexible and adaptive to evolving requirements and emerging technologies.
Major tasks:
Contribute to the development and maintenance of RESTful APIs and backend services using Node.js and Python.
Support implementation of data pipelines for telemetry validation and ingestion.
Assist in cloud-based deployments and testing of services on AWS.
Contribute to building simple ML-based features under guidance from senior engineers.
Participate in PoC development and testing for AI/ML and automation use cases.
Abl to write clean, maintainable code following Git-based version control practices.
Debug and troubleshoot application issues with guidance from team members.
Collaborate with cross-functional teams to understand requirements and implement features.
Support data-related tasks including data retrieval, transformation, and validation.
Document technical work and assist in preparing presentations or reports when required.
