Job Title

About UptimeAI:UptimeAI is leading the way in predictive analytics and AI-driven solutions to optimize operational uptime and reduce downtime for industrial and enterprise clients. Our innovative platform harnesses cutting-edge data science to deliver actionable insights, ensuring maximum efficiency and reliability. UptimeAI uniquely combines Artificial Intelligence with Subject Matter Knowledge from 200+ years of cumulative experience to explain interrelations across upstream/downstream equipment, adapt to changes, identify problems, and give prescriptive diagnosis like a human expert would. Recently receiving a funding round led by WestBridge Capital, UptimeAI is prime for global expansionRole : Data Scientist - Agentic AI, Full-Stack EngineeringLocation: Bangalore- Karnataka (Hybrid)Experience: 3+ yearsDepartment: Data ScienceWe are looking for a unique breed of Data Scientist who thrives at the intersection of Agentic AI, Full-Stack Engineering, and Industrial Design Thinking. Sitting within the Data Science team, you will be the bridge between algorithmic research and tangible product impact. You aren't just building models in a vacuum; you are leveraging modern AI-native development tools (Claude Code, Cursor, Antigravity) to rapidly build integrated, production-grade prototypes that translate complex industrial data into intuitive, actionable AI experiences.ResponsibilitiesRapid DS Prototyping: Take early-stage ML models and RAG pipelines and transform them into interactive, full-stack /"Alpha/" products within days.Agentic UX Design: Architect front-end interfaces that allow users to interact with Agentic Workflows—designing how a plant engineer /"talks/" to a Root Cause Analysis (RCA) agent or probes a time-series plot.Data Translation: Deep-dive into customer datasets (SCADA, DCS, IoT) to perform exploratory data analysis (EDA) and immediately reflect those insights in a functional UI.Bridge to Engineering: Work with core Data Science to understand model constraints and with Engineering to ensure your high-fidelity prototypes are architected for scale (API-first, containerized).Design-Led Data Science: Apply design thinking to industrial problems, ensuring our AI solutions solve the right operational workflows (e.g., maintenance scheduling, process stability).Key SkillsVelocity-First Development: Expert proficiency in Cursor/Antigravity or similar AI-integrated IDEs to bypass boilerplate and build integrated features at 10x speed.The DS Stack: Strong foundation in Python, Polars/Pandas, and Scikit-learn. You should be comfortable enough with ML to tweak a model or optimize a RAG prompt.Industrial Intuition: You /"get/" the domain—you understand that a 2% drift in a sensor might be a critical failure or just noise, and you know how to design a UI that communicates that nuance.Full-Stack Data Ownership: You are comfortable managing the data flow from a PostgreSQL/TimescaleDB backend through a FastAPI layer and into a polished frontend.Product Sense: You can sit with a customer, look at their /"messy/" data, and sketch a solution that solves their pain point before the meeting ends.Qualifications3+ years of experience in a role that blended Data Science with Software Engineering (e.g., ML Engineer, Product Engineer, or DS Prototyper).A portfolio demonstrating end-to-end AI applications—we want to see things you’ve built that people have actually clicked on.Prior experience in Industrial AI, Manufacturing, or Energy is highly preferred.A /"Hacker/" mindset: You love finding the shortest path between a complex data problem and a working solution