Role mandate

Build applied AI and digital R&D; capabilities that create defensible product intelligence for NIDOs automation platforms, moving ideas from experiment to validated pilot and then into production ownership.

What success looks like
Create a focused AI/digital R&D; roadmap tied to NIDO products and customer problems.
Deliver validated POCs/pilots in vision, optimisation, predictive intelligence and related areas.
Establish a repeatable experiment prove value pilot product decision productionise process.
Transfer successful capabilities cleanly to Product Management and NIDO OS/Controls for industrialisation.
Avoid AI for AIs sake; demonstrate measurable product/customer value.

Key responsibilities
Identify high-value AI/ML, computer vision, optimisation, simulation/digital-twin and predictive use cases.
Lead rapid experimentation, dataset strategy, model evaluation and technical feasibility work.
Develop prototypes and pilot integrations with NIDO OS, Controls, sensors/cameras and test rigs.
Define success metrics, validation plans, compute/data requirements and deployment constraints.
Build partnerships with specialist vendors, universities or external experts where faster than internal build.




Document and transfer validated technology into production teams with transparent requirements and limitations.
Maintain awareness of relevant technology shifts without chasing low-value trends.

Critical interfaces

Product Management & NPD • NIDO OS / Product Software • Controls Engineering • Systems Engineering • Reliability & Validation • Advanced Engineering & Physical R&D;

Ideal candidate profile

Hands-on applied AI/ML or computer-vision leader who has built real-world systems, preferably where software interacts with physical equipment, cameras, sensors, industrial data or operations.

Experience & qualifications
1015+ years technology experience with 5+ years in applied AI/ML/vision or advanced digital R&D.;
Evidence of deployed or pilot-stage industrial/commercial AI, not only research or dashboards.
Robust Python/ML ecosystem knowledge; architecture understanding; edge/real-time exposure preferred.
Experience with computer vision, optimisation, anomaly detection, simulation or predictive systems relevant to automation is valuable.

📌 Head Artificial Intelligence And Digital R & D Nashik (India)
🏢 Nido Machineries
📍 India