Product Intern - Machine Learning & Gen-AI - 26126
Description
Product Intern - Machine Learning & Gen-AI
Location: Bangalore (Hybrid)
Location: Bangalore (Hybrid)
Duration: 6 Months
Why YOU want this position
At Enverus, we’re committed to empowering the global quality of life by helping our customers make energy affordable and accessible to the world.
We are the most trusted energy-dedicated SaaS company, with a platform built to maximize value from generative AI, and our innovative solutions are reshaping the way energy is consumed and managed. By offering anytime, anywhere access to analytics and insights, we’re helping our customers make better decisions that help provide communities around the world with clean, affordable energy.
The energy industry is changing fast. But we’ve continued to lead the way in energy technology, creating intelligent connections across the entire energy ecosystem, from renewables, power and utilities, to oil and gas and financial institutions. Our solutions create more efficient production and distribution, capital allocation, renewable energy development, investment and sourcing, and help reduce costs by automating crucial business operations. Of course, this wouldn’t be possible without our people, which is why we have built a team of individuals from a diverse range of backgrounds.
Are you ready to help power the global quality of life? Join Enverus, and be a part of creating a brighter, more sustainable tomorrow.
At Enverus, we’re committed to empowering the global quality of life by helping our customers make energy affordable and accessible to the world.
We are the most trusted energy-dedicated SaaS company, with a platform built to maximize value from generative AI, and our innovative solutions are reshaping the way energy is consumed and managed. By offering anytime, anywhere access to analytics and insights, we’re helping our customers make better decisions that help provide communities around the world with clean, affordable energy.
The energy industry is changing fast. But we’ve continued to lead the way in energy technology, creating intelligent connections across the entire energy ecosystem, from renewables, power and utilities, to oil and gas and financial institutions. Our solutions create more efficient production and distribution, capital allocation, renewable energy development, investment and sourcing, and help reduce costs by automating crucial business operations. Of course, this wouldn’t be possible without our people, which is why we have built a team of individuals from a diverse range of backgrounds.
Are you ready to help power the global quality of life? Join Enverus, and be a part of creating a brighter, more sustainable tomorrow.
About the Role
As a Machine Learning & Generative AI Intern, you will play a hands-on role in developing and enhancing AI‑driven solutions that address real business challenges. You will collaborate with experienced ML engineers and data scientists to build models, experiment with cutting‑edge generative AI techniques, and contribute to intelligent product features. This internship offers an opportunity to deepen your technical skills while working on impactful, production‑focused AI initiatives.
Key Responsibilities
- Assist in developing machine learning and AI-based solutions
- Work on generative AI use cases such as text analysis, summarization, or chatbot-style applications
- Help clean, prepare, and analyze datasets
- Support model testing, evaluation, and performance improvement
- Contribute to experiments and proof-of-concepts of Ideas
- Communicate findings clearly with both technical and business team
Required Skills
- Understanding of core machine learning concepts
- Strong Python & ML/AI model development skills
- Introduction agentic workflows, prompt engineering, retrieval-augmented generation (RAG), and building AI agents using LLM frameworks
- Working knowledge of Git
- Strong problem-solving and analytical thinking
- Preferred Qualifications
- Prior Internships or Academic/personal projects in ML or AI
- Experience with fine‑tuning language models (LLMs) or custom model training is a strong plus