Associate Professor (AI, Robotics, IIoT) – B.Tech Program – BLR – Salary as per industry norms

Angel and Genie; Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Angel and Genie seeks an accomplished academic leader to join as Associate Professor and anchor the B.Tech in Artificial Intelligence, Robotics & IIoT. You will bridge rigorous theory with hands-on automation, owning the core engineering spine from PLCs and sensors to ROS/ROS2, edge computing, digital twins, and predictive maintenance, in the SMC AIT-400 AI Machine Lab.

You will teach across programmes, supervise dissertations, drive lab innovations, and collaborate with industry partners to

Qualifications

• Ph.D. in AI, CS, Electronics, Electrical, Instrumentation, Mechatronics, Robotics, or allied engineering disciplines.
• First Class at Bachelor’s or Master’s level (M.E./M.Tech.).
• 8–10 years combined teaching, research, and industry experience (2+ years post-Ph.D.).
• 6+ research publications in SCI/Scopus/UGC-CARE listed journals.
• Evidence of PG dissertation supervision; Ph.D. guide status preferred.

Responsibilities

• Teach and demonstrate AI/ML, robotics, and IIoT topics with real-world applications.
• Own and deliver modules for the B.Tech in AI, Robotics & IIoT across related programs.
• Supervise postgraduate dissertations and foster research.
• Lead lab activities, ensuring 100% lab hour delivery in the state‑of‑the‑art lab.

Skills

AI & Machine Learning

Computer Vision

ROS/ROS2

Python

MLOps

IIoT

Edge Computing

Defect Detection

Education

Ph.D. in AI/CS/Engineering

First Class Bachelor/Master (M.E./M.Tech.)

8–10 years teaching/research/industry

2+ years post-PhD

6+ SCI/Scopus/UGC-CARE publications

PG supervision experience/PhD guiding

Job description

About the Role

We are seeking applied technical leaders to serve as Associate Professors and serve as the primary engineering anchors for our upcoming B.Tech in Artificial Intelligence, Robotics & IIoT.

This role bridges deep academic rigor with practical, hands-on automation expertise. The appointee will own the core engineering spine—from PLC, SCADA, sensors, and pneumatics to deep learning, ROS/ROS2, edge computing, digital twins, and predictive maintenance—delivering applied learning on our state-of-the‑art SMC Corporation AIT-400 AI Machine Lab.

Primary Programme Owned

• B.Tech — Artificial Intelligence, Robotics & IIoT (Shared teaching load across PGDM AI & ML Industrial Automation 4.0, PGDM Global, and MBA Applied AI for Automation)

Mandatory Eligibility Criteria (AICTE Level 13A1)

• Ph.D. in AI, CS, Electronics, Electrical, Instrumentation, Mechatronics, Robotics, or a closely allied engineering discipline.
• First Class at Bachelor’s or Master’s level (M.E./M.Tech.).
• 8 to 10 years of combined teaching, research, and industry experience (with a minimum of 2 years post-Ph.D.).
• 6+ research publications in SCI, Scopus, or UGC-CARE listed journals.
• Research Supervision: Evidence of PG dissertation supervision (recognized Ph.D. guide status strongly preferred).

Core Technical Competencies Required

Candidates must be able to teach and practically demonstrate skills across key domains:

• AI & Machine Learning / Vision: Deep Learning (CNNs, Transformers), MLOps, Python/PyTorch/TensorFlow, Defect Detection, and Camera Calibration.
• Robotics & Automation: Forward/Inverse Kinematics, ROS/ROS2, FANUC-class teach-pendant operation, PLC ladder logic, HMI/SCADA, SMC pneumatics/electro-pneumatics.
• IIoT, Edge & Security: Modbus, Profinet, OPC-UA, MQTT, Edge Inference, Digital Twins, Predictive Maintenance, and OT Cybersecurity (ISA/IEC 62443).

Key Performance Expectations

• Research Output: Minimum 2 Scopus/SCI indexed papers per academic year and 1 external grant proposal submitted annually (DST, SERB, AICTE, MeitY, or OEM).
• Lab Ownership: Earn SMC AIT-400 OEM Trainer Certification within 6 months and ensure 100% lab hour delivery on EXPLENET.
• Student Outcomes: Achieve ≥85% OEM/IIT Ropar credential completion rate for mentored students and source ≥40% of supervised capstone projects from live industry problems.