Senior Data Informatics Manager – AI/ML Engineering Development
Chennai, India
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingLead the vision, roadmap, and execution of enterprise AI/ML and data informatics initiatives that improve operational efficiency, decision support, and service quality.
Lead the creation of context-aware conversational systems, including RAG-enabled assistants, chatbot platforms, and knowledge-driven AI applications.
Mentor and develop high-performing teams of data scientists, ML engineers, and informatics professionals, fostering technical excellence, innovation, and business impact.
From the employer’s posting
Key Responsibilities Lead the vision, roadmap, and execution of enterprise AI/ML and data informatics initiatives that improve operational efficiency, decision support, and service quality. Drive the design, development, and deployment of advanced analytical solutions using classification, clustering, regression, time series analysis, neural networks, and statistical modeling.
Oversee the development of Generative AI and NLP-based solutions, including applications involving summarization, text mining, sentiment analysis, automation, and LLM-enabled workflows. Lead the creation of context-aware conversational systems, including RAG-enabled assistants, chatbot platforms, and knowledge-driven AI applications. Guide the implementation of multi-agent and agentic AI systems to automate complex workflows, improve orchestration, and enhance enterprise decision-making.
Establish and promote best practices across the AI/ML lifecycle, including data preparation, model development, validation, deployment readiness, performance monitoring, and continuous improvement. Mentor and develop high-performing teams of data scientists, ML engineers, and informatics professionals, fostering technical excellence, innovation, and business impact. Communicate technical strategy, solution value, and execution progress effectively to senior leaders and diverse stakeholder groups.
What you’ll bring
All qualificationsCore experience
- Master’s degree or higher in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative discipline with research focus in data mining, machine learning, text mining, databases, statistics, and forecasting.
- Master’s degree or higher in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative discipline with research focus in data mining, machine learning, text mining, databases, statistics, and forecasting.
- 5+ years of progressive experience in data science, analytics, machine learning, or informatics, including experience delivering enterprise-scale solutions.
- 5+ years of progressive experience in data science, analytics, machine learning, or informatics, including experience delivering enterprise-scale solutions.
- Demonstrated expertise in machine learning and statistical methods, including classification, clustering, regression, time series analysis, hypothesis testing, Bayesian analysis, and neural networks.
- Demonstrated expertise in machine learning and statistical methods, including classification, clustering, regression, time series analysis, hypothesis testing, Bayesian analysis, and neural networks.
Preferred experience
- Experience leading teams or mentoring technical professionals in data science, AI/ML engineering, or data informatics environments.
- Hands-on experience with LLM-powered automation, systems intelligence workflows, or agentic AI.
- Demonstrated ability to quickly adopt emerging technologies and apply them effectively to create innovative, production-relevant solutions.
Qualification wording
Master’s degree or higher in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative discipline with research focus in data mining, machine learning, text mining, databases, statistics, and forecasting.
5+ years of progressive experience in data science, analytics, machine learning, or informatics, including experience delivering enterprise-scale solutions.
Demonstrated expertise in machine learning and statistical methods, including classification, clustering, regression, time series analysis, hypothesis testing, Bayesian analysis, and neural networks.
Experience leading teams or mentoring technical professionals in data science, AI/ML engineering, or data informatics environments.
Hands-on experience with LLM-powered automation, systems intelligence workflows, or agentic AI.
Demonstrated ability to quickly adopt emerging technologies and apply them effectively to create innovative, production-relevant solutions.
Tools in this posting
- R
- SAS
- SQL
- PyTorch
- TensorFlow
- Python
Source — Tool mentions in context
- Expertise in text analytics, summarization, sentiment analysis, and unstructured data processing for real-world business applications. - Proficiency with modern analytics and ML development tools such as Python, R, SAS, TensorFlow, PyTorch, SQL, and data visualization platforms. - Strong communication and leadership capabilities, with the ability to influence technical and business stakeholders and convert complex challenges into scalable solutions.
Job description
Company Overview
Group/Division
Job Description/Preferred Qualifications
Senior Data Informatics Manager – AI/ML Engineering Development
We are seeking a highly accomplished Senior Data Informatics Manager to lead the strategy, development, and delivery of advanced AI/ML engineering solutions that enable data-driven decision-making, intelligent automation, and operational excellence across the enterprise. This leader will play a critical role in shaping and scaling solutions spanning advanced analytics, machine learning, Generative AI, NLP, large language models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI frameworks.
The ideal candidate brings a strong blend of technical depth, applied innovation, and business partnership, with a track record of delivering high-impact solutions in areas such as predictive analytics, workflow automation, quality intelligence, system intelligence, conversational AI, and enterprise data science.
Key Responsibilities
- Lead the vision, roadmap, and execution of enterprise AI/ML and data informatics initiatives that improve operational efficiency, decision support, and service quality.
- Drive the design, development, and deployment of advanced analytical solutions using classification, clustering, regression, time series analysis, neural networks, and statistical modeling.
- Oversee the development of Generative AI and NLP-based solutions, including applications involving summarization, text mining, sentiment analysis, automation, and LLM-enabled workflows.
- Lead the creation of context-aware conversational systems, including RAG-enabled assistants, chatbot platforms, and knowledge-driven AI applications.
- Guide the implementation of multi-agent and agentic AI systems to automate complex workflows, improve orchestration, and enhance enterprise decision-making.
- Partner closely with cross-functional stakeholders across engineering, operations, product, cybersecurity, and business teams to identify high-value opportunities and translate them into scalable AI/ML solutions.
- Establish and promote best practices across the AI/ML lifecycle, including data preparation, model development, validation, deployment readiness, performance monitoring, and continuous improvement.
- Mentor and develop high-performing teams of data scientists, ML engineers, and informatics professionals, fostering technical excellence, innovation, and business impact.
- Communicate technical strategy, solution value, and execution progress effectively to senior leaders and diverse stakeholder groups.
Required Qualifications
- Master’s degree or higher in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative discipline with research focus in data mining, machine learning, text mining, databases, statistics, and forecasting.
- 5+ years of progressive experience in data science, analytics, machine learning, or informatics, including experience delivering enterprise-scale solutions.
- Demonstrated expertise in machine learning and statistical methods, including classification, clustering, regression, time series analysis, hypothesis testing, Bayesian analysis, and neural networks.
- Strong experience with Generative AI technologies, including LLMs, OpenAI tools, NLP techniques, LangChain, LangGraph, AutoGen, swarm or multi-agent frameworks, and vector database-based architectures.
- Proven experience building or leading solutions involving RAG, advanced chatbots, knowledge-aware AI systems, and intelligent workflow automation.
- Expertise in text analytics, summarization, sentiment analysis, and unstructured data processing for real-world business applications.
- Proficiency with modern analytics and ML development tools such as Python, R, SAS, TensorFlow, PyTorch, SQL, and data visualization platforms.
- Strong communication and leadership capabilities, with the ability to influence technical and business stakeholders and convert complex challenges into scalable solutions.
Preferred Qualifications
- Experience leading teams or mentoring technical professionals in data science, AI/ML engineering, or data informatics environments.
- Hands-on experience with LLM-powered automation, systems intelligence workflows, or agentic AI.
- Demonstrated ability to quickly adopt emerging technologies and apply them effectively to create innovative, production-relevant solutions.
Minimum Qualifications
- Master’s degree or higher in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative discipline with research focus in data mining, machine learning, text mining, databases, statistics, and forecasting.
- 5+ years of progressive experience in data science, analytics, machine learning, or informatics, including experience delivering enterprise-scale solutions.
- Demonstrated expertise in machine learning and statistical methods, including classification, clustering, regression, time series analysis, hypothesis testing, Bayesian analysis, and neural networks.
- Strong experience with Generative AI technologies, including LLMs, OpenAI tools, NLP techniques, LangChain, LangGraph, AutoGen, swarm or multi-agent frameworks, and vector database-based architectures.
We offer a competitive, family friendly total rewards package. We design our programs to reflect our commitment to an inclusive environment, while ensuring we provide benefits that meet the diverse needs of our employees.
KLA is proud to be an equal opportunity employer
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Source & posting history
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- Pay
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- Location & working pattern
Chennai, India
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- Status in our records
- Active
- First seen by us
- May 4, 2026
- Recorded sightings
- 165
- Last seen by us
- Oct 9, 2026
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