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HCLTech

Senior Technical Lead Traditional ML

HCLTech · Noida, Uttar Pradesh, India

Full-timeOn-sitePosted 13 October 2026
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Job description

Design and Develop AI/ML solutions using enterprise approved tools/technologies.Develop reusable AI capabilities (“skills”) such as copilots, agents, APIs, and domain-specific automation components for enterprise use.Build and operationalize AI-powered skills including coding assistants, recommendation engines, search assistants, and workflow automation tools.Develop and implement efficient Retrieval-Augmented Generation (RAG) model-based generative AI solutions, including text-to-code, diagram-to-code, text-to-recommendations, and diagram-to-recommendations services.Implement AI-based searches, chatbots, and APIs to enhance user experience and functionality.Design and develop generative AI, Open API, Large Language Models (LLM), RAG, or AI agent-based implementations.Utilize vector databases and indexing techniques to optimize AI solutions.Work in cloud environments such as Azure (preferred) or AWS (acceptable) to deploy and manage AI solutions.Experience designing or implementing agent-based AI systems, including:Tool invocation and function callingMulti-step decision and reasoning chainsAutonomous task execution and completionFamiliarity with agent orchestration frameworks or patterns like LangGraph, AutoGen or Crew AI. Key Responsibilities 1. Develop and implement time series forecasting models using Python, scikit-learn, TensorFlow, and StatsModels, optimizing for accuracy and scalability. 2. Integrate and process large-scale streaming data with Apache Kafka and Spark, enabling real-time model training and inference. 3. Evaluate machine learning models using cross-validation, ROC/AUC, Precision/Recall, F1-score, and confusion matrix to ensure robust predictive performance. 4. Apply advanced NLP techniques with NLTK and SpaCy to extract and preprocess relevant features for forecasting tasks. 5. Optimize model deployment pipelines using Apache Airflow and Hadoop, ensuring efficient workflow orchestration and data management. 6. Collaborate within the development team to troubleshoot, refine, and enhance ML solutions, ensuring adherence to best practices and coding standards. Skill Requirements 1. Advanced Proficiency In Machine Learning And Natural Language Processing, With Solid Experience In Time Series Analysis And Forecasting. 2. Strong Skills In Python Programming, Including Numpy, Pandas, Scikitlearn, Tensorflow, Pytorch, Xgboost, And Lightgbm. 3. Indepth Knowledge Of Distributed Data Processing With Apache Spark And Realtime Data Integration Using Apache Kafka. 4. Solid Understanding Of Ml Model Evaluation Metrics And Techniques, Including Crossvalidation And Performance Optimization. 5. Experience With Workflow Orchestration Tools Such As Apache Airflow And Big Data Platforms Like Hadoop. 6. Advanced Proficiency In Nlp Libraries Including Nltk And Spacy. Other Requirements 1. Optional But Valuable: 2. Certifications Such As Tensorflow Developer Certificate 3. - Aws Certified Machine Learning � Specialt Apply now Information at a Glance Why HCLTech? At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first. HCLTech is a global technology company, home to more than 223,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending June 2026 totaled $14.8 billion. Disclaimer Privacy Statement Terms of use Sitemap Raise a Grievance We use cookies on our site. Please read more about cookies policy here. Opens in a new tab. Opens in a new tab. Opens in a new tab. Opens in a new tab. Opens in a new tab. Opens in a new tab. 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