Senior AI Engineer

Company: ArcelorMittal Location: Hyderabad, India (Hybrid – 4 days WFO / 1 day WFH)

About ArcelorMittal

ArcelorMittal is one of the world's leading integrated steel and mining companies, operating in 60 countries with primary steelmaking in 15, and serving industries such as automotive, construction, energy, and engineering with over 125,000 employees globally.

About the Role

As a Senior AI Engineer, you will design, build, and operate production-grade AI systems end to end for one of the world's largest steel and mining companies. This role sits at the intersection of machine learning, software engineering, and enterprise delivery, working across both up-to-date GenAI/LLM systems and classical ML/DL applications. You will operate with a high degree of independence, owning solutions from problem framing through to production deployment.

What You Will Do

1. Design and implement end-to-end AI solutions from problem framing to production
2. Build and operate LLM-powered systems (prompting, RAG, agents, evaluation, guardrails)
3. Develop, train, and deploy ML/DL models where appropriate (forecasting, anomaly detection, computer vision)
4. Translate business problems into robust,



measurable AI use cases
5. Collaborate with data engineers, software engineers, and domain experts
6. Ensure AI solutions are reliable, scalable, secure, and maintainable
7. Contribute to AI architecture, best practices, and reusable components
8. Support monitoring, evaluation, and continuous improvement of AI systems

What We're Looking For

1. 6+ years of experience in AI, machine learning, or applied data science roles
2. Strong programming skills in Python
3. Hands-on experience with ML/DL frameworks and libraries
4. Experience working with API-based LLMs and modern GenAI patterns (e.g., RAG, multi-agent systems)
5. Solid software engineering fundamentals (modularity, testing, version control)
6. Experience deploying and operating AI systems in production
7. Ability to work independently, structure work, and manage risks proactively
8. Strong problem-solving and system design skills
9. Preferred: experience with enterprise data platforms and ERP integrations (e.g., SAP), cloud/MLOps tooling, computer vision/time series/optimization, and responsible AI/governance exposure

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