Industrial AI Engineer
Bengaluru, Karnataka, India
- Experience
- 2–4 years
- Employment
- Full-time
- Work mode
- Onsite
- Salary
- ₹4.6 L–5.6 L / year
- Deadline
- Apply by 1 Nov 2026
- Posted
- 2026-05-21
Required skills
| Skill | Experience | Level |
|---|---|---|
| Python | 2+ years | Intermediate |
| Application Lifecycle Management | 2+ years | Intermediate |
| FastAPI | 1+ years | Intermediate |
| Flask | 1+ years | Intermediate |
| SLM | 1+ years | Intermediate |
| Natural Language Processing | 2+ years | Intermediate |
| Machine Learning | 2+ years | Intermediate |
| Artificial Intelligence | 2+ years | Intermediate |
About the role
rganization ParyAI Solutions Pvt Ltd
Job ID JID025017
Designation Industrial AI Engineer
Experience
Minimum 2 years of experience in SLM and Python
programming
Qualification Graduate/ Postgraduate in any field
Desired skills
• Problem-solving mindset for debugging hardwaresoftware integration issues
• Self-starter capable of researching the latest papers in
SLM and Quantization
Job location Raghuvanahalli, Kanakapura Road, Bengaluru, Karnataka
CTC 4.0-6.0 LPA
Contact number 9008981927 / 8147928988
Email id hr@paryai.ai /arjun@paryai.ai
Website www.paryai.ai
• We request interested candidates to send resume through mail to the above
mentioned mail IDs only
Please mention above mentioned “Job ID” in the mail subject
Job Role – Industrial AI Engineer
We are looking for a skilled Python Programmer with a strong background in Machine
Learning and Natural Language Processing (NLP). Your primary objective will be to
design, fine-tune, and deploy Small Language Models (SLMs)
SLM Development & Fine-Tuning
• Select appropriate open-source Small Language Models (e.g., Microsoft Phi-3,
Mistral, Llama-3 8B, Gemma) suitable for edge deployment or on-premise servers.
• Fine-tune models using our proprietary operational manuals, historical sensor
logs, and troubleshooting guides to create a domain-expert AI.
• Implement RAG (Retrieval-Augmented Generation) pipelines to allow the AI to
access real-time PLC/SCADA data and static documentation simultaneously.
Python Programming & Backend
• Develop robust Python microservices (FastAPI/Flask) to host the model and serve
inference requests.
• Write efficient scripts for data pre-processing: cleaning time-series data from
sensors and converting it into textual context for the SLM.
Integration
• Build interfaces to ingest data from industrial protocols (Modbus, MQTT, OPC UA).
• Ensure the SLM allows for "Chat-with-your-Plant" functionality
Optimization & Edge Deployment
• Optimize models for low-latency inference using quantization (GGUF, AWQ) and
ONNX runtime.
• Ensure the system can run on edge devices (e.g., Industrial PCs) with limited
compute resources.