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AI/ML Architect | 13 to 17 YoE | US-headquartered Cloud, Data and AI Services Organisation | Bangalore/Pune (Immediate joiners)

Geektrust

5 - 10 years

Bengaluru

Posted: 15/01/2026

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Job Description

Work Location: Bangalore or Pune, in a hybrid work arrangement.

Experience: 13 to 17 years

Hiring Partner: Geektrust


Our customer is a cloud-focused consulting company that helps global brands solve business challenges using AI, data, and cloud-native technology. As an AI/ML Architect , you will design and deliver scalable AI, ML, and GenAI solutions on GCP by turning business problems into reliable, production-ready systems that create real business value.


What you would do:

  • Translate complex business problems into AI/ML and GenAI solution designs , selecting the right statistical, machine learning, or deep learning approaches.
  • Architect and implement cloud-native AI systems on GCP , ensuring models are scalable, secure, and production-ready.
  • Design and govern GenAI architectures , including prompt strategies, RAG-based systems, and agent-driven workflows where applicable.
  • Set technical direction and quality benchmarks for AI/ML development, influencing design decisions, tooling choices, and implementation patterns.
  • Guide teams and stakeholders through solution outcomes , reviewing models, validating assumptions, and ensuring solutions deliver measurable business value.


What you need:

  • A strong foundation in mathematics and statistics , demonstrated through formal education or extensive hands-on data science problem-solving.
  • Advanced Python expertise for AI/ML development, with R as an added advantage, and solid experience in core Python ML libraries.
  • Hands-on experience building and running AI/ML workloads on Google Cloud Platform , including model training and deployment.
  • Practical experience with Generative AI systems , such as prompt design, retrieval-augmented generation (RAG), or model fine-tuning , with Agentic AI experience.
  • Proven experience developing machine learning and deep learning solutions , using modern frameworks and production-grade practices.

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