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OnePint Software Private Limited
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OnePint Software Private Limited

https://onepint.ai
Founded :
2025
Type :
Products & Services
Size :
20-100
Stage :
Bootstrapped

About

One Pint’s AI tools for business help mid-size retailers streamline retail inventory management, cut costs, and fulfill every order promise.
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Jobs at OnePint Software Private Limited

OnePint Software Private Limited
at OnePint Software Private Limited
Praveen PC
Posted by Praveen PC
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The recruiter has not been active on this job recently. You may apply but please expect a delayed response.

Bengaluru (Bangalore)
2 - 10 yrs
₹8L - ₹35L / yr
Demand forecasting
Forecasting

Machine Learning Engineer / AI Engineer

2 to 10 Years Experience


What if your models didn't just forecast demand — they autonomously acted on it?

We're building the next generation of supply chain intelligence, where AI agents don't just predict — they reason, decide, and adapt. If you're the kind of engineer who gets excited about turning a forecast into an autonomous decision engine, this role is for you.


Be Part of Something Bigger


At our core, we own the challenge and drive the future — taking full responsibility for delivering smart, sustainable solutions that optimize supply chains. We believe knowledge fuels confidence, fostering continuous learning, innovation, and expertise to push boundaries with clarity and purpose.


With a commitment to opportunities for all and growth for everyone, we create pathways for success, empowering individuals to thrive. Our strength lies in being stronger, smarter, together — harnessing diverse perspectives and collaboration to drive bold ideas. Above all, we focus on impact that matters and results that last, building intelligent, sustainable solutions that create long-term value for businesses and the world.


What You'll Build


You'll architect intelligent systems that sense demand shifts in real time and recommend actions before a human even asks. Specifically, you will work across:


•      Agentic AI pipelines that go beyond prediction — systems that reason, decide, and adapt autonomously

•      Advanced demand forecasting and sensing models using attribute-based and cohort-based approaches

•      Signal integration frameworks that fuse external data and real-time market inputs

•      Feature engineering at scale — lag structures, rolling aggregations, and derived features

•      Model performance frameworks tied directly to measurable business outcomes

•      Translating complex model insights into clear, actionable language for clients and leadership


Who You Are


You bring a strong foundation in machine learning and a genuine curiosity about where AI is heading. The ideal candidate has:


•      2–10 years of hands-on experience in ML, AI, or Data Science with proven model-building track record

•      Python fluency — pandas, scikit-learn, XGBoost, LightGBM are second nature to you

•      Deep understanding of time series forecasting and experience with large-scale transactional datasets

•      Ability to connect model outputs to real business impact and articulate the 'so what' clearly

•      Genuine curiosity about the power of AI and openness to emerging tools and paradigms — including agentic and generative AI


Bonus Points


•      Experience in retail, supply chain, or inventory planning domains

•      Exposure to hierarchical forecasting, new product forecasting, or ensemble methods

•      Hands-on work with LLM-based agents or orchestration frameworks


Why This Role Is Different


Your models won't sit in a notebook — they'll drive decisions for real companies managing real inventory and real revenue.


•      Work at the cutting edge of agentic AI in supply chain, a space being reinvented right now

•      See your models directly influence supply chain decisions for enterprise brands, retailers, and grocers

•      Collaborate with a team of domain experts, data scientists, and product leaders who obsess over outcomes

•      Invest your curiosity in shaping how AI transforms an entire industry from the ground up


Key Performance Indicators


•      Model accuracy, reliability, and real-world forecast performance

•      Speed and quality of model deployment to production pipelines

•      Business impact of AI-driven recommendations — measured in inventory efficiency and revenue outcomes

•      Cross-functional collaboration effectiveness with product, engineering, and client teams

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