31 Text Analytics Jobs

Job description: AI/ML/Gen AI Technology Lead Location: Andheri, Mumbai Education: Bachelors or Masters degree in Computer Science, Engineering, Mathematics, or a related field with substantial experience in AI/ML engineering. Job Type: Full-Time Responsibilities: 1) Experience in programming languages such as Python, R, or Java. Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of deep learning, image processing, video analytics, and NLP techniques. 2) Experience in AI/ML Model Development, Agentic AI, Image Analytics, Voice Analytics, Text Analytics, Cloud & Infrastructure, Integration & Deployment. Hands on experience on implementation of LLM Models & Generative AI. 3) Hands-on experience with cloud platforms like AWS and Azure, including: AWS: Amazon SageMaker, AWS Lambda, AWS Glue, Amazon Redshift. Azure: Azure Machine Learning, Azure Databricks, Azure Synapse Analytics, Azure Cognitive Services. If interested, please share cv on priya@hrworksindia.com

An AI Data Scientist at IBM is not just a job title - its a mindset. Youll leverage the watsonx,AWS Sagemaker,Azure Open AI platform to co-create AI value with clients, focusing on technology patterns to enhance repeatability and delight clients. We are seeking an experienced and innovative AI Data Scientist to be specialized in foundation models and large language models. In this role, you will be responsible for architecting and delivering AI solutions using cutting-edge technologies, with a strong focus on foundation models and large language models. You will work closely with customers, product managers, and development teams to understand business requirements and design custom AI solutions that address complex challenges. Experience with tools like Github Copilot, Amazon Code Whisperer etc. is desirable. Success is our passion, and your accomplishments will reflect this, driving your career forward, propelling your team to success, and helping our clients to thrive. Day-to-Day Duties: Proof of Concept (POC) Development: Develop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another, particularly COBOL to JAVA through rapid prototypes/ PoC Documentation and Knowledge Sharing: Document solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members. Industry Trends and Innovation: Stay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services is a plus. Experience and working knowledge in COBOL & JAVA would be preferred Having experience in Code generation, code matching & code translation leveraging LLM capabilities would be a Big plus (e.g. Amazon Code Whisperer, Github Copilot etc.)Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI. Growth mindset: Demonstrate a growth mindset to understand clients' business processes and challenges. Experience in python and pyspark will be added advantage Preferred technical and professional experience Experience: Proven experience in designing and delivering AI solutions, with a focus on foundation models, large language models, exposure to open source, or similar technologies. Experience in natural language processing (NLP) and text analytics is highly desirable. Understanding of machine learning and deep learning algorithms. Strong track record in scientific publications or open-source communities Experience in full AI project lifecycle, from research and prototyping to deployment in production environments

About the Role We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities 1. Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. 2. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. 3. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. 4. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Spee

Job Description About the Role We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities 1. Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. 2. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. 3. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. 4. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech,

An AI Data Scientist at IBM is not just a job title - it’s a mindset. You’ll leverage the watsonx,AWS Sagemaker,Azure Open AI platform to co-create AI value with clients, focusing on technology patterns to enhance repeatability and delight clients. We are seeking an experienced and innovative AI Data Scientist to be specialized in foundation models and large language models. In this role, you will be responsible for architecting and delivering AI solutions using cutting-edge technologies, with a strong focus on foundation models and large language models. You will work closely with customers, product managers, and development teams to understand business requirements and design custom AI solutions that address complex challenges. Experience with tools like Github Copilot, Amazon Code Whisperer etc. is desirable. Success is our passion, and your accomplishments will reflect this, driving your career forward, propelling your team to success, and helping our clients to thrive. Day-to-Day Duties: Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another, particularly COBOL to JAVA through rapid prototypes/ PoC Documentation and Knowledge SharingDocument solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members. Industry Trends and InnovationStay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services is a plus. Experience and working knowledge in COBOL & JAVA would be preferred Having experience in Code generation, code matching & code translation leveraging LLM capabilities would be a Big plus (e.g. Amazon Code Whisperer, Github Copilot etc.) * Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI. Growth mindsetDemonstrate a growth mindset to understand clients' business processes and challenges. Experience in python and pyspark will be added advantage Preferred technical and professional experience ExperienceProven experience in designing and delivering AI solutions, with a focus on foundation models, large language models, exposure to open source, or similar technologies. Experience in natural language processing (NLP) and text analytics is highly desirable. Understanding of machine learning and deep learning algorithms. Strong track record in scientific publications or open-source communities Experience in full AI project lifecycle, from research and prototyping to deployment in production environments

Title : Senior Manager -Data Science, Machine Learning and GenAI Technical Leader Job Area: Information Technology Group, Information Technology Group > IT Management General Summary: Experience in engaging with business and technical stakeholders, understanding complex problem statements, and proposing value-driven Data Science & ML solutionsFunctional & technical leadership in developing data science roadmap and guiding the team with end-to-end delivery (design, development, maintenance, and optimization) of advanced analytical solutions with focus on process standardization and best practicesProactive in reaching out to wide variety of stakeholders for increasing the awareness of Data Science, ML and GenAI capabilities and identifying business value driven opportunitiesAnalyze the market and industry trends in the technology and proactively look for opportunities in bringing the best solutions 'Strong analytical skills with the ability to gather information from several sources and identify fundamental patterns/trends in dataConduct research, design statistical studies and develop solutionsDevelop Story Telling dashboards on analytics to assist business in decision makingImplement deep learning models for structured and unstructured data setsPerform Time Series Analysis and Forecast (ARIMA, Exponential Smoothing, VAR etc.)Implementation experience with identifying, prototyping, developing and delivering GenAI solutions using Industry standard RAG models and frameworksAbility to develop capabilities in Text Analytics ranging from Basic to Advanced (Topic Modelling, NLP)Experience with AWS suite of Data Science and ML toolsDevelops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, Catboost etc.) 'Experience with other cloud platforms (GCP and Azure)Understanding of Data Platforms and Data EngineeringExposure to ChatBot solutions and Automation technologies Minimum Qualifications: 7+ years of IT-related work experience with a Bachelor's degree. OR 9+ years of IT-related work experience without a Bachelors degree. 4+ years in a leadership role in projects/programs.

An AI Data Scientist at IBM is not just a job title - it’s a mindset. You’ll leverage the watsonx,AWS Sagemaker,Azure Open AI platform to co-create AI value with clients, focusing on technology patterns to enhance repeatability and delight clients. We are seeking an experienced and innovative AI Data Scientist to be specialized in foundation models and large language models. In this role, you will be responsible for architecting and delivering AI solutions using cutting-edge technologies, with a strong focus on foundation models and large language models. You will work closely with customers, product managers, and development teams to understand business requirements and design custom AI solutions that address complex challenges. Experience with tools like Github Copilot, Amazon Code Whisperer etc. is desirable. Success is our passion, and your accomplishments will reflect this, driving your career forward, propelling your team to success, and helping our clients to thrive. Day-to-Day Duties: Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another, particularly COBOL to JAVA through rapid prototypes/ PoC Documentation and Knowledge SharingDocument solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members. Industry Trends and InnovationStay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services is a plus. Experience and working knowledge in COBOL & JAVA would be preferred o Having experience in Code generation, code matching & code translation leveraging LLM capabilities would be a Big plus (e.g. Amazon Code Whisperer, Github Copilot etc.) Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI. Growth mindsetDemonstrate a growth mindset to understand clients' business processes and challenges. Experience in python and pyspark will be added advantage Preferred technical and professional experience ExperienceProven experience in designing and delivering AI solutions, with a focus on foundation models, large language models, exposure to open source, or similar technologies. Experience in natural language processing (NLP) and text analytics is highly desirable. Understanding of machine learning and deep learning algorithms. Strong track record in scientific publications or open-source communities Experience in full AI project lifecycle, from research and prototyping to deployment in production environments

An AI Engineer at IBM is not just a job title - it's a mindset. You'll leverage the watsonx platform to co-create AI value with clients, focusing on technology patterns to enhance repeatability and delight clients. Success is our passion, and your accomplishments will reflect this, driving your career forward, propelling your team to success, and helping our clients to thrive. Day-to-Day Duties: Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Collaboration and Project ManagementCollaborate with cross-functional teams, including data scientists, software engineers, and project managers, to ensure smooth execution and successful delivery of AI solutions. Effectively communicate project progress, risks, and dependencies to stakeholders. Customer Engagement and SupportAct as a technical point of contact for customers, addressing their questions, concerns, and feedback. Provide technical support during the solution deployment phase and offer guidance on AI-related best practices and use cases. Documentation and Knowledge SharingDocument solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members. Industry Trends and InnovationStay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise EducationBachelor's, Master's, or Ph.D. degree in Computer Science, Artificial Intelligence, Data Science or a related field. Technical Skills: Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services is a plus. Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI. Growth mindsetDemonstrate a growth mindset to understand clients' business processes and challenges. Preferred technical and professional experience ExperienceProven experience in designing and delivering AI solutions, with a focus on foundation models, large language models, exposure to open source, or similar technologies. Experience in natural language processing (NLP) and text analytics is highly desirable. Understanding of machine learning and deep learning algorithms.

An AI Data Scientist at IBM is not just a job title – it’s a mindset. You’ll leverage the watsonx,AWS Sagemaker,Azure Open AI platform to co-create AI value with clients, focusing on technology patterns to enhance repeatability and delight clients. We are seeking an experienced and innovative AI Data Scientist to be specialized in foundation models and large language models. In this role, you will be responsible for architecting and delivering AI solutions using cutting-edge technologies, with a strong focus on foundation models and large language models. You will work closely with customers, product managers, and development teams to understand business requirements and design custom AI solutions that address complex challenges. Experience with tools like Github Copilot, Amazon Code Whisperer etc. is desirable. Success is our passion, and your accomplishments will reflect this, driving your career forward, propelling your team to success, and helping our clients to thrive. Day-to-Day Duties: Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another, particularly COBOL to JAVA through rapid prototypes/ PoC Documentation and Knowledge SharingDocument solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members. Industry Trends and InnovationStay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise New WatsonX Assistant with phone integration 2. WatsonX Assistant Extensions 3. Requirement Analysis, Solution Design, and CDD Creation (nice to have) Experience and working knowledge in COBOL & JAVA would be preferred Having experience in Code generation, code matching & code translation leveraging LLM capabilities would be a Big plus (e.g. Amazon Code Whisperer, Github Copilot etc.) Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI. Growth mindsetDemonstrate a growth mindset to understand clients' business processes and challenges. Experience in python and pyspark will be added advantage Preferred technical and professional experience ExperienceProven experience in designing and delivering AI solutions, with a focus on foundation models, large language models, exposure to open source, or similar technologies. Experience in natural language processing (NLP) and text analytics is highly desirable. Understanding of machine learning and deep learning algorithms. Strong track record in scientific publications or open-source communities Experience in full AI project lifecycle, from research and prototyping to deployment in production environments

Some careers shine brighter than others. If you re looking for a career that will help you stand out, join HSBC and fulfil your potential. Whether you want a career that could take you to the top, or simply take you in an exciting new direction, HSBC offers opportunities, support and rewards that will take you further. HSBC is one of the largest banking and financial services organisations in the world, with operations in 64 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realise their ambitions. We are currently seeking an experienced professional to join our team in the role of Consultant Specialist. In this role, you will: Configure and manage users access to reports and dashboards. Create management dashboards and reports on Key Performance Indicators (KPIs) and metrics, ensure the accuracy and integrity of data used in reports and dashboards. Answer key business questions to help increase quality. Provide real-time visibility into data and predictive forecasts for enhanced decision-making. Utilize text analytics to extract trends and patterns from freeform data fields. Proficiency with ServiceNow Workbench for interactive filtering, Breakdowns and end-to-end transparency. Provide users with professional consultation and guidance. Take ownership of assigned tasks and execute them as per agreed timelines. Requirements To be successful in this role, you should meet the following requirements: ITSM Knowledge ServiceNow platform knowledge ServiceNow Scripting (Java Script) Glide API Knowledge Experience in working on various reports and dashboard. Strong understanding of data analysis techniques, including statistical methods and programming Excellent communication and problem-solving skills are also vital for translating complex data into actionable insights, driving process improvements, and making informed decisions.

Job Responsibilities: Build and deploy GenAI Models with techniques such as RAG and Fine Tuning. Developing AI/ML algorithms to analyze huge volumes of historical data to make predictions and recommendations. Implement and optimize deep learning models for generative tasks such as image synthesis, voice etc Collaborate with software engineers to integrate Generative AI models into production systems Should be able evaluate the application cases and problem-solving potential of AI/ML algorithms and rank them according to success likelihood. Should be able to comprehend data through exploration and visualization, spot discrepancies in data distribution Should be able to work on structured as well as unstructured data Should be able to develop various algorithms based on statistical modelling procedures and build and maintain scalable machine learning solutions in production Should be able to leverage cloud platforms for training and deploying large scale solutions (AWS Preferred) Should have working knowledge on managing ModelOps framework Should understand CI/CD processes in product deployment and used it in delivery. Should be able to collaborate with data engineers to build data and model pipelines and maintain accuracy Should be able to take complete ownership of the assigned project Experience of working in Agile environments Well versed with JIRA or equivalent project tracking tool Competencies / Skills Understanding of AI/ML frameworks,LLM libraries, data structures, data modeling, and software architecture. Proficiency with a deep learning framework such as TensorFlow, Keras, NLP and text analytics and ML algorithms like clustering, regression, classification etc Proficiency with Python and basic libraries for machine learning such as scikit-learn, pandas Experience working with recommendation engines, data pipelines and distributed machine learning Ability to select hardware to run an ML model with the required latency Knowledge of cloud platforms (AWS, Azure and GCP) Great communication and collaboration skills.

Role Overview: We' re looking for a Lead Data Scientist to join our fast-growing, mission-driven team. This is a high-impact leadership role at the intersection of technology, strategy, and innovation where your expertise will power intelligent solutions that redefine how we think about data, products, and customer experience. If you thrive in high-performance environments and want to lead cutting-edge projects with Generative AI, LLMs, and large-scale NLP systems, this is your opportunity to make a lasting impact. Key Responsibilities: Build the Future with AI/ML Architect scalable AI systems to solve real-world, high-value business challenges cross domains. Design and deploy cutting-edge solutions with Generative AI, Transformer architectures, and custom Large Language Models (LLMs). Apply state-of-the-art ML techniques prompt engineering, transfer learning, multi-modal learning to push the boundaries of what's possible. NLP at Scale Lead the development of advanced NLP systems: semantic search, question answering, summarization, classification, and conversational AI. Work with best-in-class models and libraries: BERT, GPT, RoBERTa, Word2Vec, SpaCy, NLTK, Hugging Face Transformers, and more. Leverage language understanding to transform unstructured data into strategic insights. Full-Lifecycle Model Deployment Build robust MLOps pipelines for training, testing, deployment, and monitoring using MLflow, Kubeflow, Airflow, and CI/CD tools. Containerize and orchestrate AI models using Docker and Kubernetes across cloud environments (AWS, GCP, Azure). Design APIs and inference services using FastAPI or gRPC, optimized for performance, scalability, and uptime. Lead, Inspire, and Elevate Build and mentor a world-class data science team, nurturing talent and fostering a culture of curiosity, experimentation, and technical excellence. Drive the data science strategy, influence key decisions, and align AI initiatives with business goals. Establish best-in-class practices for model development, code quality, documentation, and performance evaluation. Data at the Core Work hands-on with structured, semi-structured, and unstructured data. Optimize high-volume data pipelines, integrate with SQL and NoSQL databases, and leverage big data ecosystems like Spark, Hive, and Hadoop. Use statistical modeling and experimental design to derive actionable intelligence from data Collaborate Across the Enterprise Work closely with engineering, product, and executive teams to define problems, explore solutions, and deliver AI products that move the needle. Translate technical concepts into strategic recommendations and insights that influence roadmaps and revenue. Champion AI literacy and advocate for ethical, explainable, and scalable data science across the organization. Education Bachelors or Master’s in Computer Science, AI, Data Science, Machine Learning, Engineering, or a related technical discipline. PhD is a plus. Experience 6+ years of experience in data science or machine learning, with 2+ years in a leadership or managerial role. Proven record of building and deploying AI solutions at scale in real-world production environments. Experience in GenAI, NLP, cloud-native architectures, and full-cycle ML development. Technical Expertise Languages & Libraries: Python, Scikit-learn, PyTorch, TensorFlow, Hugging Face, NumPy, Pandas NLP: BERT, GPT, Word2Vec, SpaCy, NLTK, TextBlob, CoreNLP, Transformer-based architectures Cloud & Deployment: AWS, Azure, GCP, Docker, Kubernetes, FastAPI, gRPC Big Data: Spark, Hive, Hadoop, Kafka Data Systems: PostgreSQL, MongoDB, Cassandra, Snowflake, BigQuery MLOps & Monitoring: MLflow, Airflow, Kubeflow, Prometheus, Grafana Nice to Have Experience in online reputation management, customer analytics, or product-led organizations. Familiarity with responsible AI, fairness, and explainability techniques (SHAP, LIME).

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

We are seeking an experienced and innovative AI Solution Engineer to be specialized in foundation models and large language models. In this role, you will be responsible for architecting and delivering AI and Automation solutions using cutting-edge technologies, with a strong focus on foundation models and large language models. In this role, you will be resposible for : Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Customer Engagement and SupportAct as a technical point of contact for customers, addressing their questions, concerns, and feedback. Provide technical support during the solution deployment phase and offer guidance on AI-related best practices and use cases. Industry Trends and InnovationStay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Bachelor’s or Master's degree in Computer Science, Artificial Intelligence, or a related field. 4+ years of experience in designing and delivering AI solutions, with a focus on foundation models, large language models, or similar technologies. Experience in natural language processing (NLP) and text analytics is highly desirable. Technical Skills: Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and related services is a plus. Solutioning ExperienceExperience in solution architecture and design, translating business requirements into technical specifications, and developing scalable and robust AI solutions. Business AcumenAbility to understand customer needs and business objectives. Experience in working closely with customers and translating their requirements into effective AI solutions. Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI. Growth mindsetDemonstrate a growth mindset to understand clients’ business processes and cha Preferred technical and professional experience Experience in full AI project lifecycle, from research and prototyping to deployment in production environments. Familiarity with Agile development methodologies Experience with AI and/or data governance Experience with building business automation or digital labor solutions Experience with building customer care solutions/digital assistants Experience with Red Hat OpenShift Experience with Kubernetes Experience with vector DB’s or open file formats like parquet ,avro or orc

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

Job Responsibilities. Hands on (Full Stack) SaaS application design and development concentrating on Artificial intelligence using big data technologies.. Facilitate solution efficiencies, scalability and technology stack leadership.. Ensure fool proof and robust applications through unit tests and other quality control measures. Follow an agile development process, and enable rapid solutions to business challenges.. Take inputs from internal and external clients and constantly strive to improve solutions.. Setup and following software design, development, testing and documentation best practices.. Extract and parse data from online and local data sources; Clean up data, audit data for accuracy, consistency and completeness.. Apply analytics and artificial intelligence techniques and extract valuable and actionable insights. Data processing and visualization:Summarize insights in simple yet powerful charts, reports, slides, etc.. For internal and external client projects, use our proprietary tools for performing data engineering, analytics and visualization activities. Responsible for project deliveries, escalation, continuous improvement, and customer success.. Candidate Profile. Strong knowledge of Python, Django, React, Flask, Flutter, Bootstrap, HTML,CSS, Javascript, SQL.. Expertise in Full Stack Web Application development is required.. Proficiency in software development:Conceptualizing, Designing, Coding, debugging.. Prior Background in AI, ML, Deep Learning, Image processing and computer vision is preferred.. Strong in algorithm design, database programming (RDBMS), and text analytics.. Knowledge of MongoDB, Redis, Docker, Containerization, Kubernetes, AWS, Kafka is preferred. High problem-solving skills:able to logically breakdown problems into incremental milestones, prioritize high impact deliverables first, identify bottlenecks and work around them.. Self-learner:highly curious, self-starter and can work with minimum supervision and guidance.. Entrepreneurial mind set with a positive attitude is a must.. Track record of excellence in academics or non-academic areas, with significant accomplishments.. Qualifications. E / B. 3 to 8 years of relevant experience. (ref:hirist.tech).

ob Description Role: AI Developer Agentic AI Exp: 2-3 Years Work Mode: 1210 pm, Onsite( Mohali, Punjab) Job Role & Responsibilities Design, develop, and deploy Agentic AI systems capable of autonomous task execution by integrating reasoning, memory, and tool use to enable intelligent behavior across complex, multi-step workflows, Architect intelligent agents that can dynamically interact with APIs, data sources, and third-party tools to accomplish diverse objectives with minimal human intervention, Optimize performance of agentic frameworks by enhancing model accuracy, minimizing response latency, and ensuring scalability and reliability in real-world applications, Develop reusable, testable, and production-grade code, adhering to best practices in software engineering and modern AI development workflows, Collaborate with cross-functional teams, including product managers, designers, and backend engineers, to convert business requirements into modular agent behaviors, Integrate Retrieval-Augmented Generation (RAG), advanced NLP techniques, and knowledge graph structures to improve decision-making and contextual awareness of agents, Conduct rigorous profiling, debugging, and performance testing of agent workflows to identify bottlenecks and improve runtime efficiency, Write and maintain comprehensive unit, integration, and regression tests to validate agent functionality and ensure robust system performance, Continuously enhance codebases, refactor existing modules, and adopt new design patterns to accommodate evolving agentic capabilities and improve maintainability, Implement secure, fault-tolerant, and privacy-compliant designs to ensure that deployed agentic systems meet enterprise-grade reliability and data protection standards, Qualification Required Bachelors degree in computer science, or related field, Specialization or Certification in AI or ML is a plus, Technical Expertise 2+ years of hands-on experience in AI/ML/DL projects, with a strong emphasis on Natural Language Processing (NLP), Named Entity Recognition (NER), and Text Analytics, Proven ability to design and deploy Agentic AI systems?autonomous, goal-oriented agents that exhibit reasoning, memory retention, tool use, and execution of multi-step tasks, Practical expertise in agent architecture, task decomposition, and seamless integration with external APIs, databases, and tools to enhance agent capabilities, Skilled in agent prompting strategies, including dynamic prompt chaining and context management, to guide language models through intelligent decision-making workflows, Experience with Retrieval-Augmented Generation (RAG) pipelines and generative AI, with a strong focus on optimizing NLP models for low-latency, high-accuracy production use, Solid foundation in deep learning methods, recommendation engines, and AI applications within HR or similar domains, Exposure to Reinforcement Learning (RL) frameworks and holds relevant certifications or specializations in Artificial Intelligence, showcasing continuous learning and depth in the field, Minimum Skills We Look For Skills & Expertise (with Agentic AI focus) Proven experience in building Agentic AI systems, including autonomous agents capable of multi-step reasoning, memory management, and tool use, Expertise in agent design patterns, task decomposition, dynamic planning, and decision-making logic using LLMs, Skilled in integrating multi-agent coordination, goal-setting, and feedback loops to create adaptive, evolving agent behavior, Strong command over prompt engineering, contextual memory structuring, and tool calling mechanisms within LLM-powered agent workflows, Proficiency in managing agent memory (short-term, long-term, episodic) using vector databases and custom memory stores, Ability to build autonomous task execution pipelines with minimal human input, combining language models, APIs, and third-party tools, Experience with frameworks and orchestration for agent behavior tracing, logging, and failure recovery, Tools & Technologies Agentic AI Agentic Frameworks: LangChain, CrewAI, AutoGen, AutoGPT, BabyAGI for building, managing, and orchestrating intelligent agents, LLM APIs: OpenAI (GPT-4/3 5), Anthropic (Claude), Cohere, Hugging Face Transformers, Memory & Vector Databases: FAISS, Weaviate, Pinecone, Chroma for embedding-based agent memory and contextual retrieval, Prompt Management Tools: PromptLayer, LangSmith for testing, evaluating, and refining agent prompts and traces, RAG & Context Enrichment: LangChain RAG pipelines, Haystack, Milvus, Autonomy Infrastructure: Docker, FastAPI, Redis, Celery for building scalable agent runtimes, Observability: OpenTelemetry, Langfuse (or similar) for tracing agent decisions, failures, and success metrics, Testing Agentic Behavior: Integration with PyTest + mock APIs/tools to validate autonomous decision logic and fallback strategies,

As a Data Scientist within the Product Analytics team, you will leverage data to identify "aha!" moments and enable business breakthroughs. You will be central in understanding investment customers financial needs and interactions with our products, services, channels, and Advisors. Job Responsibilities Search for collections of behaviors and events to enable timely, relevant outreach. Analyze drivers of sales team performance to understand acquisition, deepening, and retention outcomes. Predict a segment s unique financial needs to improve engagement with new clients. Overlay customer and channel behaviors to optimize staffing. Provide expertise in data visualization, machine learning, and text analytics/NLP to optimize sales performance. Create self-serve tools for real-time decision-making. Identify potential attrition events and determine effective counteraction timing. Required Qualifications, Capabilities, and Skills Unique combination of technical skills, mathematical know-how, storytelling, and intuition. Programming skills in R, Python, and Java for computational aspects and statistical models. Ability to apply machine learning, deep learning, and AI technologies appropriately. Problem-solving focus beyond model performance curves. Independent and collaborative thinking to implement creative solutions. Ability to summarize key information and present recommendations to influence senior management. Preferred Qualifications, Capabilities, and Skills Experience in insights functions at financial services, consulting firms, or marketing agencies. Experience in workforce analytics, sales performance analytics, or sales science organizations. Proficiency in big data disciplines, Agile methodologies, and new technologies. Proficiency with BI tools like Tableau and Shiny Dashboards.

Responsibilities: * Design generative AI solutions using LLM, Python, SQL & NLP techniques. * Collaborate with cross-functional teams on project delivery. * Implement RNN, LSTM, GRU models for text analysis.

Travel Partnerships and Media helps partners, including hotels, airlines, destination marketing organizations (DMOs) and more, deliver excellent traveler and B2B experiences. we'drive growth for our partners and the Expedia Group marketplace through competitive supply, our leading advertising and travel media network and affiliate solutions. The TPM Partner Journeys team is accountable for the overall experience of TPM supply partners. This team takes a holistic, macro-level approach to define and drive experience improvements across EG. We are responsible for measuring the partners overall experience, accounting for all touchpoints, and delivering insights to drive actionable improvements. As an Insight Analyst - Partner Journeys , you will leverage advanced analytics and AI to transform partner data into actionable insights within the TPM Partner Journeys team. As part of this team accountable for the overall experience of TPM supply partners, you will help establish foundational analytics frameworks while driving improvements in the partner experience and supporting Expedias strategic objectives through data-driven recommendations. In this role, you will: Apply analytical techniques to structured and unstructured data across holistic, cross-channel partner journeys to extract meaningful insights, identifying opportunities to reduce friction, increase revenue, and enhance satisfaction. Develop compelling data stories and visualizations that effectively communicate key journey insights and actionable recommendations to diverse stakeholders, helping drive experience improvements across Expedia Group. Establish foundational measurement frameworks to consistently evaluate partner experiences across all touchpoints, creating a comprehensive view of the partner journey. Leverage cutting-edge technologies including LLMs, generative AI, and text analytics platforms to analyze qualitative feedback, uncover sentiment patterns, and accelerate insight production. Establish and maintain robust insight production processes that support the Experience Management schedule, ensuring timely delivery of partner insights that drive actionable improvements. Collaborate with cross-functional teams to translate partner journey insights into strategic recommendations, helping the TPM Partner Journeys team fulfill its mission of holistic experience improvement. Experience and Qualifications: Bachelors degree in any technical discipline (eg, Analytics, Data Science, Engineering, Computer Science, Mathematics, Statistics) with 3+ years of experience in customer/partner experience analytics or similar data-focused roles. Strong experience generating insights from cross-channel partner journeys , with the ability to identify patterns across multiple touchpoints and build foundational analytics frameworks in evolving business environments. Expert-level data storytelling capabilities - demonstrated mastery in transforming complex data into compelling, action-oriented narratives that resonate with stakeholders and drive strategic business decisions. Advanced proficiency in data visualization and reporting tools (eg, Tableau, PowerBI , Looker) with exceptional ability to design intuitive dashboards that effectively communicate insights from complex partner journeys, with experience using conversation intelligence platforms like Zoom Revenue Accelerator or Gong being a plus . Experience utilizing text analytics platforms, survey tools, and CX management systems such as Qualtrics XMD or Medallia , with working knowledge of project management tools like Jira and Confluence being advantageous . Excellent communication and collaborative skills, with the proven ability to help establish new analytics processes and evangelize insights across organizational boundaries, ideally complemented by consulting experience and knowledge of AI/ML technologies , particularly generative AI or large language models (LLMs).