AI/ML Engineer
Intuitive.ai
2 - 5 years
Ahmedabad
Posted: 21/03/2026
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Job Description
About us:
Intuitive is an innovation-led engineering company delivering business outcomes for 100s of Enterprises globally. With the reputation of being a Tiger Team & a Trusted Partner of enterprise technology leaders, we help solve the most complex Digital Transformation challenges across following Intuitive Superpowers:
Modernization & Migration
- Application & Database Modernization
- Platform Engineering (IaC/EaC, DevSecOps & SRE)
- Cloud Native Engineering, Migration to Cloud, VMware Exit
- FinOps
Data & AI/ML
- Data (Cloud Native / DataBricks / Snowflake)
- Machine Learning, AI/GenAI
Cybersecurity
- Infrastructure Security
- Application Security
- Data Security
- AI/Model Security
SDx & Digital Workspace (M365, G-suite)
- SDDC, SD-WAN, SDN, NetSec, Wireless/Mobility
- Email, Collaboration, Directory Services, Shared Files Services
Intuitive Services:
- Professional and Advisory Services
- Elastic Engineering Services
- Managed Services
- Talent Acquisition & Platform Resell Services
About the job:
Title: AI/ML Engineer
Start Date: Immediate
Position Type: Full Time
Location: Ahmedabad, India
- Design, develop, and deploy machine learning solutions to address diverse business challenges, leveraging 35 years of handson experience in productiongrade ML systems.
- Demonstrate strong expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks.
- Collaborate with data scientists and engineering teams to gather, clean, and preprocess structured and unstructured datasets.
- Analyze datasets to uncover trends, correlations, and actionable insights that guide model development.
- Build, train, and optimize machine learning algorithms and statistical models tailored to specific business needs.
- Evaluate and validate model performance using metrics, experiments, and cross-validation techniques.
- Communicate insights, model outputs, and project progress effectively to technical and nontechnical stakeholders.
- Stay current with emerging AI/ML techniques, tools, and industry trends to continuously enhance the organization's capabilities.
- Develop robust endtoend ML pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring.
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