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Data Science Manager - Artificial Intelligence / Machine Learning

Data Science Manager - Artificial Intelligence / Machine Learning

Chargeback GurusChennai
14 days ago
Job description

Description : Job brief :

An ideal candidate will have 7 to 12 years of experience working in live projects related to Artificial :

  • Lead the design and implementation of enterprise-grade Machine Learning, Deep Learning and Generative AI solutions.
  • Define and execute the AI technology projects, aligning Generative AI, Machine Learning, and Deep Learning initiatives with business strategy and data architecture.
  • Design, evaluate, and guide development of autonomous and agentic AI systems capable of reasoning, planning, and tool-based decision-making.
  • Architect end-to-end RAG pipelines including document processing, embedding generation, vector storage, retrieval mechanisms, and contextual response systems.
  • Oversee Machine Learning and Deep Learning model development, training, deployment, and optimization for predictive and generative use cases.
  • Establish robust LLMOps / MLOps pipelines ensuring model lifecycle management, observability, version control, and performance monitoring.
  • Collaborate with data engineering, analytics, and DevOps teams to integrate AI systems with enterprise data warehouse / lakes, APIs, and reporting environments.
  • work with stakeholders to identify, evaluate, and prioritize AI-driven business opportunities, focusing on measurable impact and innovation.
  • Provide technical leadership, mentorship, and guidance to AI engineers, data scientists, and developers, fostering a high-performance innovation culture.
  • Stay ahead of emerging AI research, frameworks, and tools, driving continuous evolution of enterprise AI capabilities.

Skills Areas :

  • Deep expertise in Generative AI, Large Language Models (GPT, Claude, Llama, Mistral, etc.), and RAG architectures.
  • Strong proficiency in Agentic AI concepts - autonomous agents, multi-agent orchestration, and reasoning loops.
  • Advanced understanding of Machine Learning (ML) and Deep Learning (DL) algorithms, architectures (Transformers, CNNs, RNNs), and model deployment workflows.
  • Experience architecting solutions with AWS agentic AI framework, LangChain, LlamaIndex, Semantic Kernel, or similar frameworks.
  • Hands-on experience with RDBMS, No SQL and vector databases.
  • Proficiency in Python, scikit-learn, PyTorch, TensorFlow, and Hugging Face Transformers.
  • Expertise in LLMOps / MLOps practices model training, CI / CD, observability, and drift management.
  • Deep understanding of cloud-native AI architecture (AWS Sagemaker, Azure AI, GCP Vertex AI).
  • Strong foundation in AI governance, ethical AI, and compliance frameworks.
  • Excellent leadership, communication, and stakeholder management skills to align AI initiatives with business goals.
  • Good-to-Have Skills :

  • Experience in Data Engineering ETL / ELT pipeline design, data modeling, data warehousing, and integration with AI pipelines.
  • Familiarity with Data Visualization and BI tools such as Power BI, Tableau, Amazon QuickSight especially for building analytical insights from AI-driven data.
  • Understanding of DataOps and analytics architectures supporting AI and decision intelligence systems.
  • Knowledge of enterprise data platforms and API-based data integration to connect AI models with structured and unstructured data sources.
  • Experience :

  • The ideal candidate will have relevant experience of > 7 years.
  • Possession of a professional degree / post-graduation is desirable.
  • Certifications in the respective technology areas will be an added advantage.
  • (ref : hirist.tech)

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