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📍 Location: Bangalore (On-site)
📅 Duration: 6 Months
🚀 About Us
At EMO Energy, we’re building next-generation EV and energy technologies. As we expand our software and intelligence stack, we’re integrating AI/ML to enable smarter energy systems, predictive insights, automation, and enhanced product workflows. If you’re excited about applying AI in real-world engineering environments, this is the place to learn and build.
⚡ Job Summary
We are looking for an AI and ML Engineer - Intern who will work on data analysis, model development, and integrating ML-powered features into our platforms. You will collaborate with backend and product teams to build lightweight ML pipelines, experiment with cloud AI tools, and support ongoing AI/automation initiatives.
🎯 What You Will Do
- Analyse battery datasets (voltage, current, capacity, cycles) to extract insights.
- Detect charging, discharging, and idle modes using data-driven logic.
- Develop and evaluate ML models (Regression, Boosting, MLP).
- Engineer features like power, rolling stats, dV/dt, dI/dt, and mode flags.
- Preprocess time-series data and handle outliers, noise, and inconsistencies.
- Create clear visualizations (time-series, scatter, comparison plots).
- Document analysis steps, model results, and key findings.
- Integrate ML outputs into scripts or backend APIs with guidance.
- Explore cloud AI or LLM APIs (Vertex AI, OpenAI) for internal tools.
- Collaborate with Engineering teams on data-driven workflows.
- Final-year students pursuing AI/ML,Computer Science, Data Science Engineering, or related fields.
- Strong Python fundamentals and understanding of ML workflows.
- Familiarity with Scikit-learn, Pandas, NumPy, and basic deep learning frameworks.
- Understanding of regression models and evaluation metrics.
- Ability to work with time-series data and engineer meaningful features.
- Good analytical and debugging skills with eagerness to learn.
- Bonus: Exposure to energy systems or battery datasets.
- Work on real-world EV and energy datasets.
- Build ML pipelines that support live engineering systems.
- Hands-on exposure to cloud platforms and modern AI tools.
- Fast-paced learning environment with mentorship from experienced engineers.
- Opportunity for full-time conversion based on performance.
Key Skills
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