AI/ML Engineer

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.