Applied AI Researcher - Energy Intelligence Platform

Voltanova; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Health insurance

Equity

Career growth

Job summary

Voltanova seeks an Applied AI Researcher to tackle challenging problems at the intersection of machine learning, energy systems, optimization, and industrial processes. You will build intelligent models that blend weather, renewable generation, electricity demand, tariffs, grid, storage, and industrial processes to understand uncertainty and optimize decisions.

You will collaborate with energy and thermal engineering teams to translate physical constraints into intelligent models and push toward

Qualifications

• Strong foundations in ML, statistics, probability, mathematics and optimization.
• Hands-on Python programming.
• Experience with PyTorch, TensorFlow or JAX.
• Experience with time-series forecasting, probabilistic ML, reinforcement learning or mathematical optimization.

Responsibilities

• Develop advanced time-series forecasting models for energy demand, renewable generation, electricity prices, weather and other energy variables.
• Build probabilistic forecasting systems that quantify uncertainty and enable reliable energy decisions.
• Develop AI-driven optimization and decision-making for energy storage and industrial energy systems.
• Research and implement approaches using Transformers, Reinforcement Learning, Physics-Informed ML, and hybrid ML/optimization methods.

Skills

Machine Learning

Statistics

Probability

Mathematics

Optimization

Tools

PyTorch

TensorFlow

JAX

Job description

The Role

As an Applied AI Researcher, you will work on challenging problems at the intersection of machine learning, energy systems, optimization, and industrial processes.

You will build intelligent models that combine:
Weather + Renewable Generation + Electricity Demand + Tariffs + Grid + Storage + Industrial Processes

The goal is not simply to predict what happens next, but to build systems that can understand uncertainty, optimize decisions, and eventually autonomously manage energy systems.

What You ll Work On

• Develop advanced time-series forecasting models for energy demand, renewable generation, electricity prices, weather, and other energy variables.
• Build probabilistic forecasting systems that quantify uncertainty and enable reliable energy decisions.
• Develop AI-driven optimization and decision-making for energy storage and industrial energy systems.
• Research and implement approaches using Transformers, Reinforcement Learning, Physics-Informed ML, and hybrid ML/optimization methods.
• Build systems that move from: Prediction Optimization Decision Autonomous Energy Management
• Incorporate real-world physical constraints from thermal systems, energy storage, industrial processes, and power systems into ML models.
• Develop models that learn from real industrial operating data and continuously improve with deployment.
• Work closely with our energy and thermal engineering teams to translate physical constraints into intelligent models.
• Explore novel approaches to make energy optimization more accurate, robust, explainable, and computationally efficient.
• Take research ideas from hypothesis experiment validation deployment.

What We re Looking For

• Strong foundations in Machine Learning, Statistics, Probability, Mathematics, and Optimization.
• Strong Python programming skills.
• Hands-on experience with PyTorch, TensorFlow, or JAX.
• Experience with one or more of:
  • Time-series forecasting
  • Probabilistic ML
  • Reinforcement Learning
  • Mathematical optimization
  • Deep Learning
  • Control systems
• Strong research mindset and the ability to independently formulate problems, design experiments, test hypotheses, and interpret results.
• Ability to work with real-world, noisy, high-frequency, or incomplete datasets.
• Strong curiosity and willingness to work on problems where the solution may not already exist in a textbook or research paper.

What Makes This Role Different

This is not a conventional forecasting role.

You will be working toward an AI system that understands the interaction between energy, economics, weather, physical systems, and industrial operations and eventually makes autonomous decisions about when to generate, store, purchase, and consume energy.

You will work across the entire intelligence stack:
Data Prediction Uncertainty Optimization Control Autonomous Energy Decisions

You will also work directly with our engineering teams, giving you the opportunity to connect advanced ML research with real physical energy systems and industrial deployments.

What We Offer

• Competitive compensation with a significant equity package and meaningful ownership in the company s growth.
• Research ownership the opportunity to independently explore, develop, and deploy novel ML approaches to real-world energy problems.
• Work on frontier problems at the intersection of AI, energy, climate, optimization, and industrial systems.
• Direct impact your models will be applied to real energy systems and industrial operations, not just research benchmarks.
• Close collaboration with multidisciplinary experts across machine learning, thermal engineering, energy systems, and industrial technology.
• High autonomy and rapid execution freedom to experiment, challenge assumptions, and turn promising research into working systems.
• Comprehensive health insurance and a supportive work environment.
• Professional and technical growth in a fast-growing deep-tech company building for a global market.
• The opportunity to help build the AI intelligence layer for the future of industrial energy.

Why Voltanova

Energy is becoming increasingly complex.

Renewables are intermittent. Electricity prices fluctuate. Industrial processes have hard physical constraints. Energy storage introduces another layer of optimization.

The next generation of industrial energy systems will require more than hardware they will require intelligence.

At Voltanova, you will have the opportunity to build that intelligence from the ground up.

Build the AI brain that manages the future of industrial energy.