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AI ML Data Architect

Tata Consultancy Services

Pune, Maharashtra, India · 정규직

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경험
4–12 yrs
샐러리
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1
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1시간 전
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About the Company

Tata Consultancy Services is a leading IT services, consulting, and business solutions provider, partnering with some of the world's largest organizations for over 50 years. The company values innovation and collaborative knowledge to create a meaningful impact on the future.

Job Overview

We are seeking an experienced AI ML Data Architect with 4 to 12 years of relevant experience. The role is based in Pune at the TAJ Vivanta Pune Xion Complex, located in Hinjawadi Phase 1. This position involves hands-on work with Generative AI, Gemini, or open-source large language models to create solutions in code translation, text extraction, summarization, and software development lifecycle optimization.

Key Responsibilities

  • Utilize advanced Generative AI technologies and large language models for building AI applications focused on code translation, text extraction, summarization, and improving software development processes.
  • Examine, cleanse, and analyze extensive and complex datasets to identify patterns, trends, and opportunities for actionable insights.
  • Develop, train, and validate machine learning, statistical, and predictive models aimed at solving practical business challenges and generating measurable results.
  • Design and conduct experiments including A/B testing, hypothesis testing, and simulations to assess concepts, quantify results, and support informed decision-making.
  • Collaborate closely with data engineers, analysts, product managers, and domain experts to convert business needs into clear and structured modeling objectives.
  • Create end-to-end machine learning workflows from feature engineering and data preprocessing through to deployment-ready models.
  • Apply sophisticated methods such as natural language processing, time series forecasting, anomaly detection, optimization algorithms, and specialized LLM or Generative AI techniques as appropriate.
  • Develop model evaluation frameworks using offline metrics, cross-validation techniques, live experiments, and human feedback loops to ensure reliability.
  • Effectively communicate insights through interactive dashboards, visualizations, documentation, and presentations suited to both technical and non-technical audiences.
  • Guarantee model transparency by making results interpretable and explainable, highlighting key factors and underlying assumptions.
  • Partner with engineering teams to implement models in production environments, oversee performance monitoring, and manage ongoing retraining or recalibration as data evolves.

Eligibility

The position is open to candidates who have completed any graduate degree.

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