Sustainability Economics.ai
Website:
sustainabilityand.com
Company:
https://www.linkedin.com/company/sustainabilityeconomics
Seniority: Internship
Industries: Technology, Information and Internet
Job details:
Location: Bengaluru, Karnataka
Internship Type: Full-time, On-site
Duration: 6 months (Full-time conversion based on performance)
About the Company
Sustainability Economics.ai is a global organization pioneering the convergence of clean energy and AI, enabling profitable energy transitions while powering end-to-end AI infrastructure. By integrating AI-driven cloud solutions with sustainable energy, we create scalable, intelligent ecosystems that drive efficiency, innovation, and long-term impact across industries. Guided by exceptional leaders with deep expertise across finance, policy, and technology, we are committed to building impactful, future-ready solutions.
Role Summary
We are looking for a curious and motivated Machine Learning Intern to join our team and learn alongside experienced engineers and data scientists.
This is a learning-focused role designed for someone with a strong foundation in programming, mathematics, and an interest in machine learning. You will work on real-world problems at the intersection of AI and clean energy, gaining hands-on exposure to data, models, and production-grade systems.
No prior production ML experience is required — what matters is your eagerness to learn, ability to think clearly, and willingness to take ownership of the problems you work on.
Key Responsibilities
- Support the team in day-to-day data and machine learning tasks.
- Help with data collection, cleaning, preprocessing, and exploratory analysis.
- Assist in running experiments and evaluating different modelling approaches under guidance.
- Work with senior engineers to understand how ML systems are built, tested, and deployed.
- Document your work, experiments, and findings clearly for the team.
- Contribute to internal tooling, scripts, and reproducible workflows.
- Share insights from data and present results in team discussions.
- Continuously learn — through reading, experimenting, and collaborating with the team.
Education & Experience
- Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Engineering, Applied Mathematics, Statistics, Data Science, or a related quantitative field.
- 0–1 year of experience (academic projects, coursework, hackathons, or open-source contributions are welcome).
- A solid foundation in mathematics and statistics.
- Genuine interest in machine learning and applied AI.
Skills Required
- Comfortable programming in Python and working with libraries like NumPy and Pandas.
- Familiarity with basic machine learning concepts (e.g., regression, classification, clustering).
- Awareness of how data is structured and analysed (Jupyter Notebooks, basic visualisation).
- Familiarity with Git/GitHub for version control.
- Strong problem-solving skills and attention to detail.
- Good written and verbal communication.
- A learning mindset — willingness to ask questions, take feedback, and pick up new tools quickly.
What You'll Do
- Build and deploy end-to-end ML and forecasting systems.
- Develop intelligent data pipelines for predictive and probabilistic analytics.
- Work on real-world time series problems in energy, infrastructure, and sustainability domains.
- Collaborate with engineering teams to integrate ML models into scalable systems.
- Monitor and improve model performance, accuracy, and reliability.
- Contribute to building AI-driven decision-making platforms.
What You'll Bring
- Working knowledge of ML or optimization concepts, with practical exposure through projects or coursework.
- Strong mathematical and statistical foundation.
- Passion for scalable systems, automation, and applied problem-solving.
- Startup DNA → bias to action, comfort with ambiguity, love for fast iteration, and flexible and growth mindset.
Why Join Us
- Shape a first-of-its-kind AI + clean energy platform.
- Work with a small, mission-driven team obsessed with impact.
- An aggressive growth path.
- A chance to leave your mark at the intersection of AI and sustainability.
Click on Apply to know more.
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