AI/ML Engineer - Industrial Analytics

About Tata Consultancy Services

Tata Consultancy Services (TCS) is a global IT services, consulting, and business solutions organization. With a legacy spanning over 50 years, it has supported transformation efforts for many leading businesses internationally. Leveraging a consulting-led and AI-powered portfolio, TCS delivers integrated business, technology, and engineering services through its acclaimed Location Independent Agile14 delivery model. Part of the Tata Group, India's largest multinational conglomerate, TCS employs over 616,000 consultants representing 157 nationalities across 53 countries.

Job Overview

We are seeking a full-time AI/ML Engineer based in Riyadh, KSA to design, develop, and deploy machine learning and deep learning models tailored to industrial contexts, especially those handling large-scale numerical, categorical, time series data, images, and video inputs.

Key Responsibilities

• Develop and deploy ML/DL models for complex industrial challenges involving diverse and large datasets.
• Engage in extensive Python programming for statistical analysis, custom algorithm creation, and extracting actionable business insights from ML/DL outputs.
• Apply advanced optimization techniques like Genetic Algorithms, Linear and Quadratic Programming.
• Manage complete data workflows including data gathering, exploratory analysis, cleansing, feature engineering, and rigorous model validation.
• Implement AI/ML solutions on cloud infrastructures such as Azure and AWS using MLOps practices.
• Utilize expertise in NLP, large language models, retrieval-augmented generation, and a variety of ML algorithms (Decision Trees, Clustering, SVMs, ANN, LSTM, CNN, YOLO), understanding their practical capabilities and constraints.
• Continuously acquire new knowledge and keep abreast of emerging AI/ML technologies and methodologies.

Desired Qualifications & Experience

• Demonstrable experience in deploying ML/DL solutions involving multiple data types.
• Proficiency in Python for analytics and algorithm development.
• Strong background in optimization approaches such as genetic algorithms and linear/quadratic programming.
• Familiarity with full-cycle data processes and MLOps on Azure and AWS.
• Solid grasp of NLP techniques, large language models, and a spectrum of ML algorithms.

Additional Preferred Skills

• Work experience in the oil & gas sector, refinery operations, asset monitoring, or related process industries.
• Knowledge or hands-on experience with generative AI, AI agents, retrieval-augmented generation, knowledge graphs, or hybrid physics-ML modeling techniques.
• Understanding of MLOps platforms, concept of drift detection, and principles of responsible AI.

Application Deadline

Applications must be submitted by 10-October-2026.

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