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Company Description Polrix Energy Intelligence is an AI-powered energy intelligence company that helps developers and building owners create smarter, more efficient, and future-ready buildings. The platform delivers real-time analytics, predictive insights, and intelligent energy management to optimize energy use and reduce operational costs. By integrating advanced AI and data-driven models, Polrix enables proactive decision-making for building performance and sustainability. The team focuses on scalable solutions that can be deployed across modern real estate portfolios and next-generation smart infrastructure.
Role Description This is a full-time hybrid role based in Gurugram, with flexibility for partial work from home. The Technical Co-Founder & Lead NILM Architect will lead the design, development, and deployment of core NILM (Non-Intrusive Load Monitoring) algorithms and energy intelligence architecture. Daily responsibilities include defining system architecture, building and validating ML models for load disaggregation, and collaborating with engineering teams to integrate NILM capabilities into the product stack. The role involves working closely with product and business stakeholders to translate customer needs into technical solutions, overseeing data pipelines and model performance, and ensuring scalability, reliability, and security of the energy analytics platform. As a co-founder, the person will also contribute to strategic technology decisions, team building, and long-term roadmap planning.
Qualifications
- Strong analytical skills, including data analysis, problem-solving, and the ability to interpret complex energy usage patterns.
- Effective communication skills for collaborating with cross-functional teams, presenting technical concepts clearly, and engaging with customers and partners.
- Sales and marketing awareness to support technical pre-sales discussions, product demonstrations, and positioning of NILM solutions in the market.
- Research skills for exploring new NILM methodologies, AI models, and energy management techniques, and for evaluating emerging technologies.
- Deep experience with machine learning, signal processing, or power systems engineering; prior work on NILM or related energy analytics is highly beneficial.
- Proficiency in programming languages commonly used in ML and data engineering (e.g., Python), and familiarity with cloud platforms and scalable architectures.
- Ability to work in a startup environment, taking ownership, making informed trade-offs, and mentoring a growing technical team.
- Bachelor’s or Master’s degree in Engineering, Computer Science, Data Science, or a related technical field, or equivalent practical experience.
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