305 Bert Jobs

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.Keywordsnatural language processing,machine learning,deep learning,machine learning algorithms,tensorflow,keras,artificial intelligence,Data Science Mandatory Key Skills natural language processing,machine learning,deep learning,machine learning algorithms,tensorflow,keras,artificial intelligence,Data Science*

Execute end-to-end Data Science projects including data collection, preprocessing, feature engineering, modelling, evaluation, and deployment. Design and implement advanced Machine Learning algorithms (classification, regression, clustering, ensemble methods) and Natural Language Processing algorithms (Knowledge Graphs, Topic Modelling, Feature Extraction, Sentiment Analysis, BERT etc.) Develop and deploy Generative AI and LLM-based solutions using platforms like OpenAI, Hugging Face, and LLama. Apply Agentic AI frameworks such as LangChain, LangGraph, Crew AI, or Microsoft Semantic Kernel to build intelligent applications. Proficient in designing and deploying scalable machine learning solutions using cloud architectures, with hands-on experience in at least one major platform (Azure, AWS, GCP, or IBM Cloud). Skilled in leveraging Databricks, ML platforms, managed databases, web hosting services, and document AI tools for end-to-end solution development. Collaborate with business stakeholders to define problem statements, deliver insights, and drive impact. Maintain reproducibility and version control using Git, GitHub Effectively communicate technical concepts and project outcomes to both technical and non-technical stakeholders. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 7–9 years of hands-on experience in Data Science, Machine Learning, Deep Learning, and NLP in a production environment. 2+ years of applied experience in Generative AI and LLMs (e.g., OpenAI, LLama). Proficiency in agentic AI development using frameworks like LangChain, LangGraph, or similar. Strong programming skills in Python and experience with ML/DL libraries Experience deploying models via REST APIs or web applications. Proficient in SQL for data extraction, transformation, and analysis. Experience working with large datasets, feature engineering, and data preprocessing pipelines. Solid understanding of model evaluation, cross-validation, and performance metrics. Experience in MLOps, including model testing, deployment pipelines, governance frameworks, and continuous monitoring for reliable and compliant machine learning operations. Experience with cloud ML pipelines and services (proficiency in at least one of Azure, AWS, GCP & IBM Cloud). Strong interpersonal and client communication skills.

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. Mandatory Key Skillsnatural language processing,BERT,GPT,LSTMs,machine learning,Data Science*

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. Mandatory Key Skillsnatural language processing,lstm,machine learning,bert,gpm,deep learning,machine learning algorithms,algorithms,information extraction,python,tensorflow,keras,artificial intelligence,Data Science*

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. Mandatory Key SkillsNLP,machine learning,bert,gpm,deep learning,text analytics,sentiment analysis,machine learning algorithms,information extraction,python,TensorFlow,keras,artificial intelligence,Data Science*

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. Mandatory Key Skillsnatural language processing,machine learning,deep learning,text analytics,machine learning algorithms,information extraction,tensorflow,keras,artificial intelligence,Data Science*

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. Mandatory Key Skillsnatural language processing,machine learning,deep learning,text analytics,sentiment analysis,machine learning algorithms,algorithms,information extraction,BERT,GPT,LSTM,NLP*

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. Mandatory Key Skillsnatural language processing,machine learning,deep learning,text analytics,sentiment analysis,machine learning algorithms,algorithms,information extraction,python,data science,tensorflow,keras,artificial intelligence,NLP modelling*

Key Responsibilities: Architect, build, and deploy scalable GenAI applications using OpenAI, and Retrieval-Augmented Generation (RAG) techniques. Design and orchestrate modular, reproducible, and robust data pipelines leveraging Kedro for end-to-end machine learning workflows. Integrate LangChain to develop advanced natural language workflows and enhance AI-powered applications. Take GenAI prototypes from concept to production, ensuring reliability, scalability, and maintainability in real-world environments. Containerize machine learning and GenAI solutions with Docker for seamless deployment and scalability across cloud and on-premises platforms. Collaborate with cross-functional teamsincluding Engineering, Product, and Operationsto align AI solutions with business goals and deliver measurable impact. Mentor and support junior team members, sharing best practices in data science, MLOps, and GenAI deployment. Continuously evaluate and implement emerging AI technologies, driving innovation and excellence in our AI capabilities. Key Qualifications: 4+ years of experience in GenAI, data science, machine learning, or AI-focused roles. 2+ years of experience in GenAI. Advanced proficiency in Python; extensive experience with OpenAI APIs, and other modern LLMs. Strong background in Retrieval-Augmented Generation (RAG) methods and architectures. Proven expertise with LangChain for natural language processing and workflow automation. Demonstrated experience taking GenAI prototypes to production environments. Experience building and orchestrating data pipelines with Kedro. Proficient in Docker-based containerization and deployment (Kubernetes a plus). Knowledge of data engineering and software engineering best practices. Excellent communication, collaboration, and mentoring skills. Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. Experience with working on SQL DB like Postgres and No-SQL DB like MongoDB Preferred Qualifications: Experience with AWS or other major cloud platforms. Experience with CI/CD tools and automated testing frameworks. Open-source contributions, technical presentations, or publications in AI/ML. Previous leadership or mentorship of technical teams. Building Backend Python APIs.

Job Title: Principal Data Scientist Location: Noida Employment Type: Full-time Responsibilities: Convert broad vision and concepts into a structured data science roadmap and guide a team to successfully execute on it Collaborate with AI Product managers, UI/UX, stakeholders, etc. to design, develop, and deploy AI/LLM models Good in fine-tuning, and optimization of LLMs like Open AI, Gemini AI, Copilot, and open-source models like LLAMA, DeepSeek, and BERT Hands-on experience in Prompt Engineering and RAG for real-world applications Develop Conversational AI, ChatBots, VoiceBots using modern NLP frameworks like SpaCy, Rasa, LangChain, Hugging Face Use vector databases like Pinecone, Vertex AI, ChromaDB, or SingleStore to manage embeddings at scale Deploy and monitor models on cloud platforms like Azure and GCP Lead client engagements, RFP responses generation, and PoC development for both internal and external stakeholders Provide technical guidance, code reviews, and performance optimization support Expertise in designing solutions using semantic search and vector embeddings Translate high-level business goals into measurable, AI-powered deliverables Proven ability to discover solutions hidden in large datasets and to drive business results with their data-based insights Contribute to internal product development initiatives related to data science. Drive excellent project management skills required to deliver complex projects, including effort/time estimation Be proactive, with full ownership of the engagement. Build scalable client engagement level processes for faster turnaround & higher accuracy Qualifications: A B.Tech / M.Tech / MBA from a top tier Institute preferably in a quantitative subject 10+ years of hands-on experience in applied Machine Learning, AI and analytics Experience of scientific programming in scripting languages like Python, R, SQL, NoSQL, Spark with ML tools & Cloud Technology (AWS, Azure, GCP) Expertise in Python libraries such as numpy, pandas, scikit-learn, tensor-flow, scrapy, BERT etc. Strong expertise in Machine Learning, Deep Learning, Data mining, and Statistical concepts and experience in developing models and solutions in these areas Expertise in client engagement, understanding complex problem statements, and offering solutions in the domains of Supply Chain, Manufacturing, CPG, Marketing etc. Strong publication record in top-tier journals and conferences. Functional thought leader, sought after for key tech decisions. Can successfully sell ideas to an executive level decision maker. Mentors and trains the research scientist community on complex technical issues. Experience developing software in traditional programming languages (C++, Java, etc..). Excellent written and spoken communication skills About Us E-Solutions is a leading AI consulting firm delivering cutting-edge solutions across recruitment & staffing, IT services, finance, retail, education, and manufacturing. We specialize in building advanced AI/ML products including large-scale recommender systems, LLM-based chatbots, AI-powered resume engines, GenAI copilots, and enterprise-wide automation systems. As part of our growing AI leadership team, we are looking for a Principal Data Scientist who can architect, lead, and implement end-to-end AI/ML solutions using the latest in Generative AI, LLMs, Vector Databases, and NLP frameworks. Reimagine the Future of IT Consulting & Development with ML, GenAI, & Agentic AI At E-Solutions, we empower global businesses by enhancing their IT infrastructure and software capabilities. Over two decades, weve grown into a trusted global partner, operating in 35+ countries with a team of 5,000+ professionals. Our expertise in Managed IT Services and Software Product Engineering, combined with robust testing, cloud solutions and AI/ML/Gen AI in NLP & Computer Vision domains ensures that the enterprise thrives in a competitive digital landscape. E-Solutions has achieved significant success in implementing ML/GenAI/Agentic AI projects like AI enabled matching of professionals profiles based on customer requirements, Agentic AI based end-to-end recruitment platform which will process & summarize customer requirements and AI agent will conduct online interviews and have efficient assessment to retrieve relevant profiles, Conversational AI Engine, Detecting Suspicious Behaviour during interviews etc. Simultaneously, the company successfully executed mergers and acquisitions, driving significant growth and expansion and embarking on a transformative digital journey. Join us to be the part of this innovative journey to build cutting-edge advance Agentic AI platform to deliver AI/ML/GenAI use cases across industries. Show more Show less

Job Title: Lead Data Scientist Location: Noida Employment Type: Full-time Responsibilities: Lead and manage a team of data scientists, providing guidance, mentorship, and technical expertise Collaborate with stakeholders to understand business objectives and develop data science strategies aligned with those objectives Design, develop, and implement advanced machine learning and statistical models to solve complex business problems. Conduct exploratory data analysis, data cleansing, and feature engineering to prepare datasets for analysis. Good in fine-tuning, and optimization of LLMs like Open AI, Gemini AI, Copilot, and open-source models like LLAMA, DeepSeek, and BERT Hands-on experience in Prompt Engineering and RAG for real-world applications Develop Conversational AI, ChatBots, VoiceBots using modern NLP frameworks like SpaCy, Rasa, LangChain, Hugging Face Use vector databases like Pinecone, Vertex AI, ChromaDB, or SingleStore to manage embeddings at scale Deploy and monitor models on cloud platforms like Azure and GCP Lead client engagements, RFP responses generation, and PoC development for both internal and external stakeholders Provide technical guidance, code reviews, and performance optimization support Explore and utilize various data mining and machine learning techniques to extract valuable insights and patterns from large datasets. Develop predictive/prescriptive models, algorithms, and prototypes to support business. Communicate findings and insights to technical and non-technical stakeholders through reports, presentations, and data visualizations. Play an active role in software development processes. Stay up to date with the latest trends and advancements in data science, machine learning, and AI technologies and identify opportunities to apply them to improve business outcomes. Qualifications: A B.Tech / M.Tech / MBA from a top tier Institute preferably in a quantitative subject 5+ years of hands-on experience in applied Machine Learning, AI and analytics with a proven track record of developing AI/LLM models and algorithms A masters or bachelors degree in data science, Computer Science, Statistics, or a related field Strong programming skills in scripting languages like Python, R, SQL, NoSQL, Spark with ML tools & Cloud Technology (AWS, Azure, GCP) Expertise in Python libraries such as numpy, pandas, scikit-learn, tensor-flow, scrapy, BERT etc. Strong expertise in Machine Learning, Deep Learning, Data mining, and Statistical concepts and experience in developing models and solutions in these areas Expertise in client engagement, understanding complex problem statements, and offering solutions in the domains of Supply Chain, Manufacturing, CPG, Marketing etc. Strong publication record in top-tier journals and conferences. Functional thought leader, sought after for key tech decisions. Can successfully sell ideas to an executive level decision maker. Mentors and trains the research scientist community on complex technical issues. Experience developing software in traditional programming languages (C++, Java, etc..). Excellent written and spoken communication skills About Us E-Solutions is a leading AI consulting firm delivering cutting-edge solutions across recruitment & staffing, IT services, finance, retail, education, and manufacturing. We specialize in building advanced AI/ML products including large-scale recommender systems, LLM-based chatbots, AI-powered resume engines, GenAI copilots, and enterprise-wide automation systems. As part of our growing AI leadership team, we are looking for a Principal Data Scientist who can architect, lead, and implement end-to-end AI/ML solutions using the latest in Generative AI, LLMs, Vector Databases, and NLP frameworks. Reimagine the Future of IT Consulting & Development with ML, GenAI, & Agentic AI At E-Solutions, we empower global businesses by enhancing their IT infrastructure and software capabilities. Over two decades, weve grown into a trusted global partner, operating in 35+ countries with a team of 5,000+ professionals. Our expertise in Managed IT Services and Software Product Engineering, combined with robust testing, cloud solutions and AI/ML/Gen AI in NLP & Computer Vision domains ensures that the enterprise thrives in a competitive digital landscape. E-Solutions has achieved significant success in implementing ML/GenAI/Agentic AI projects like AI enabled matching of professionals profiles based on customer requirements, Agentic AI based end-to-end recruitment platform which will process & summarize customer requirements and AI agent will conduct online interviews and have efficient assessment to retrieve relevant profiles, Conversational AI Engine, Detecting Suspicious Behaviour during interviews etc. Simultaneously, the company successfully executed mergers and acquisitions, driving significant growth and expansion and embarking on a transformative digital journey. Join us to be the part of this innovative journey to build cutting-edge advance Agentic AI platform to deliver AI/ML/GenAI use cases across industries. Show more Show less

As an Associate Consultant/Consultant, you will play a crucial role in designing and implementing AI/ML models and data-driven solutions to tackle intricate challenges in healthcare and life sciences. Your responsibilities will include analyzing large datasets to identify trends, generate insights, and support data-informed decision-making. Additionally, you will collaborate with consultants, data engineers, and scientists to establish end-to-end data pipelines and analytical workflows. Your key responsibilities will involve: - Designing and implementing AI/ML models and data-driven solutions for complex challenges in healthcare and life sciences - Analyzing large datasets to identify trends, generate insights, and support data-informed decision-making - Collaborating cross-functionally with consultants, data engineers, and scientists to build end-to-end data pipelines and analytical workflows - Engaging with clients through interviews, workshops, and presentations to contribute to deliverables and foster strong relationships - Communicating complex analyses into clear, actionable insights for both technical and non-technical stakeholders - Continuously learning about AI/ML advancements, contributing to research and proposals, and mentoring junior team members Qualifications required for this role include proficiency in Machine Learning, Python, Gen AI, and Consulting/Stakeholder Management. Desirable technical skills encompass proficiency in Python, experience with frameworks like TensorFlow, PyTorch, or scikit-learn, working with generative AI models such as GPT, BERT, LLaMA, or other transformer-based architectures, developing, testing, and deploying high-quality AI models and solutions, data manipulation, cleaning, and analysis proficiency, creating clear visualizations using tools like Matplotlib, Seaborn, or Tableau, and familiarity with cloud services like AWS, Google Cloud, or Azure for deploying AI solutions.,

As a Data Science and AI / ML professional at LTIMindtree, you will play a crucial role in leveraging digital technologies to drive innovation and growth for our clients. With over 6 years of experience in the field, you will be expected to have a deep understanding of machine learning techniques and algorithms, such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests, etc. Your expertise in data frameworks like Hadoop, business intelligence tools like Tableau, and Cloud native skills will be essential in delivering superior business outcomes. Key Responsibilities: - Utilize your knowledge of SQL and Python, with familiarity in Scala, Java, or C++ as an asset, to develop innovative AI solutions - Apply your analytical mind and strong math skills in statistics and algebra to solve complex business challenges - Work with common data science toolkits such as TensorFlow, KERAs, PyTorch, PANDAs, Microsoft CNTK, NumPy, etc., with expertise in at least one being highly desirable - Leverage your experience in NLP, NLG, and Large Language Models like BERT, LLaMa, LaMDA, GPT, BLOOM, PaLM, DALL-E, etc., to drive transformative projects - Communicate effectively and present your findings with great clarity, thriving in a fast-paced team environment - Utilize AIML and Big Data technologies like AWS SageMaker, Azure Cognitive Services, Google Colab, Jupyter Notebook, Hadoop, PySpark, HIVE, AWS EMR, etc., to scale your solutions - Apply your expertise in NoSQL databases such as MongoDB, Cassandra, HBase, Vector databases to handle large datasets effectively - Demonstrate a good understanding of applied statistics skills like distributions, statistical testing, regression, etc., to derive valuable insights for the business Qualifications Required: - More than 6 years of experience in Data Science and AI / ML domain - Excellent understanding of machine learning techniques and algorithms - Experience using business intelligence tools and data frameworks - Knowledge of SQL and Python; familiarity with Scala, Java or C++ is an asset - Strong math skills (e.g., statistics, algebra) - Experience with common data science toolkits - Great communication and presentation skills - Experience with AIML and Big Data technologies - Experience with NoSQL databases Please note that the mentioned qualifications, skills, and experiences are mandatory for the role at LTIMindtree.,

Role Overview: You will be responsible for designing, building, and deploying Generative AI models using foundational models like GPT, BERT, LLaMA, PaLM, etc. Additionally, you will develop scalable GenAI applications, integrate them with enterprise systems using APIs and SDKs, and fine-tune large language models (LLMs) for domain-specific use cases. You will also design, implement, and manage end-to-end machine learning pipelines on Microsoft Azure, collaborate with data scientists to productionize ML models, and automate deployment and monitoring of models using CI/CD pipelines and Azure DevOps tools. Furthermore, you will ensure security, compliance, and governance of ML workflows and data, troubleshoot and optimize ML workflows, and document architecture, processes, and operational procedures. Key Responsibilities: - Design, build, and deploy Generative AI models using models like GPT, BERT, LLaMA, PaLM - Develop scalable GenAI applications and integrate with enterprise systems using APIs and SDKs - Fine-tune and optimize large language models (LLMs) for domain-specific use cases - Design, implement, and manage end-to-end machine learning pipelines on Microsoft Azure - Collaborate with data scientists to productionize ML models using best practices in Azure MLOps - Automate the deployment and monitoring of models using CI/CD pipelines and Azure DevOps tools - Implement scalable model training, validation, and deployment workflows in the cloud - Monitor model performance in production, retrain models as needed, and ensure security, compliance, and governance of ML workflows and data - Develop Python scripts and tools to automate tasks, troubleshoot and optimize ML workflows, and document architecture, processes, and operational procedures Qualifications Required: - Hands-on experience with transformer-based models (e.g., GPT, BERT, LLaMA, etc.) - Familiarity with tools like LangChain, LlamaIndex, Haystack, etc. - Experience in prompt engineering, retrieval-augmented generation (RAG), and model fine-tuning - Proven experience in MLOps, specifically with Azure services - Strong programming skills in Python - Experience with Hugging Face Transformers, PyTorch or TensorFlow - REST APIs and/or gRPC for model integration - Experience with Azure Databricks, Azure Machine Learning, Azure OpenAI - Familiarity with ML libraries (scikit-learn, TensorFlow, PyTorch) - Experience building and managing CI/CD pipelines for ML models using Azure DevOps or equivalent tools - Building REST APIs for ML inference using frameworks like FastAPI or Flask - Understanding of containerization technologies like Docker and orchestration using Kubernetes - Knowledge of machine learning lifecycle management, model versioning, and deployment strategies - Experience with data engineering, data pipelines, and ETL processes on Azure - Familiarity with monitoring tools and logging frameworks for production systems - Strong problem-solving skills and ability to work in a collaborative, fast-paced environment,

Role Overview: As a Senior Consultant in TMT Business Consulting Finance at EY, you will have the opportunity to work with Technology, Media & Entertainment, and Telecommunications organizations to help them evolve, transform, and stay competitive in the industry. Your role will involve creating compelling employee and customer experiences, ensuring operational excellence, safeguarding data and reputation, and supporting M&A strategies. You will play a key part in shaping the future of the technology revolution and contributing to building a better working world for all. Key Responsibilities: - Develop end-to-end GenAI solutions using LLMs (OpenAI, Claude, Llama, Gemini, etc.) - Build and manage multi-agent orchestration using frameworks like AutoGen, CrewAI, Semantic Kernel - Design document chunking, embedding, and indexing pipelines using Pinecone, Weaviate, FAISS, pgvector - Optimize RAG pipelines for latency, relevance, and safety - Create reusable prompt templates for zero-shot, few-shot, and chain-of-thought applications - Fine-tune open-source models using LoRA, QLoRA, or supervised datasets when needed - Containerize AI workflows using Docker/Kubernetes and deploy on Azure/AWS/GCP - Set up CI/CD pipelines, logging, monitoring, and automated evaluation metrics (hallucination, toxicity) - Maintain clean code, modular utilities, internal documentation, and reusable accelerator components for the GenAI Factory Qualifications Required: - 3-5 years of practical experience in building GenAI or Agentic AI applications with measurable business outcomes - Strong Python skills (asyncio, FastAPI, LangChain, Pydantic), basic JavaScript/TypeScript for integration plugins - Experience with LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, and Hugging Face ecosystem - Expertise in machine learning algorithms and deep learning techniques (e.g., BERT, GPT, LSTM, CNN, RNN) - Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field Additional Company Details: At EY, you will have the opportunity to work with over 200,000 clients globally and be part of a team of 300,000 professionals, including 33,000 individuals in India. EY is committed to investing in the skills and learning of its employees, offering personalized Career Journeys and access to career frameworks to enhance roles, skills, and opportunities. The organization is dedicated to being an inclusive employer, striving to achieve a balance between delivering excellent client service and supporting the career growth and well-being of its employees.,

As a Data Scientist at C5i, you will be part of a team that caters to some of the world's largest enterprises, including Fortune 500 companies across various sectors such as Technology, Media, Telecom, Pharma & Lifesciences, CPG, Retail, and Banking. C5i has garnered recognition from industry analysts like Gartner and Forrester for its Analytics and AI capabilities along with proprietary AI-based platforms. **Key Responsibilities:** - Possess 4+ years of experience in machine learning, deep learning, or AI research, focusing on generative models. - Demonstrated expertise in generative models including GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and transformer-based models like GPT-3/4, BERT, DALL.E. - Understanding of model fine-tuning, transfer learning, and prompt engineering within the realm of large language models (LLMs). - Knowledge of reinforcement learning (RL) and other advanced machine learning techniques applicable to generative tasks. - Proficient in Python programming and well-versed with relevant libraries and frameworks. - Proven hands-on experience in document detail extraction and feature engineering. - Proficiency in data processing and manipulation techniques. - Hands-on experience in developing data applications using Streamlit or similar tools. - Advanced knowledge in prompt engineering, chain of thought processes, and AI agents. - Strong problem-solving skills and the ability to collaborate effectively in a team environment. - Excellent communication skills to articulate complex technical concepts to non-technical stakeholders. **Qualifications Required:** - 4+ years of experience in machine learning, deep learning, or AI research, with a specific focus on generative models. - Proficiency in generative models such as GANs, VAEs, and transformer-based models. - Knowledge of reinforcement learning and advanced machine learning techniques for generative tasks. - Strong programming skills in Python and familiarity with relevant libraries and frameworks. - Proven experience in document detail extraction and feature engineering. - Hands-on experience in building data applications using Streamlit or similar tools. - Advanced knowledge in prompt engineering, chain of thought processes, and AI agents. - Strong communication skills to effectively convey technical concepts to non-technical stakeholders. Please note that the Job Description also mentions that C5i has been recognized by leading industry analysts like Gartner and Forrester for its Analytics and AI capabilities and proprietary AI-based platforms.,

Role Overview: You will be a part of the Data and Analytics (D&A) team at EY as a Senior Data Scientist. With a minimum of 3-7 years of experience in Data Science and Machine Learning, you will be involved in developing and implementing AI solutions, particularly focusing on NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. Your role will be crucial in leveraging your technical expertise to contribute to cutting-edge AI models and systems. Responsibilities: - Contribute to the design and implementation of state-of-the-art AI solutions. - Assist in the development and implementation of AI models and systems, utilizing techniques such as Language Models (LLMs) and generative AI. - Collaborate with stakeholders to identify business opportunities and define AI project goals. - Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. - Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases. - Integrate with relevant APIs and libraries like Azure Open AI GPT models and Hugging Face Transformers to enhance generative AI capabilities. - Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. - Utilize vector databases such as Redis and NoSQL databases for efficient handling of large-scale generative AI datasets. - Implement similarity search algorithms to enable efficient retrieval of information from generative AI outputs. - Collaborate with domain experts, stakeholders, and clients to tailor generative AI solutions based on specific business requirements. - Conduct research on advanced AI techniques to enhance performance and efficiency. - Establish evaluation metrics to assess the quality and relevance of generative AI outputs. - Ensure compliance with data privacy, security, and ethical considerations in AI applications. - Utilize data engineering skills for data curation, cleaning, and preprocessing for generative AI applications. Requirements: - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Ph.D. is a plus. - Minimum 3-7 years of experience in Data Science and Machine Learning. - Proficiency in programming languages like Python, R, and frameworks such as TensorFlow or PyTorch. - Strong understanding of NLP techniques and frameworks like BERT, GPT, or Transformer models. - Familiarity with computer vision techniques. - Experience with cloud platforms like Azure, AWS, or GCP for deploying AI solutions. - Knowledge of trusted AI practices ensuring fairness, transparency, and accountability. - Strong collaboration skills with software engineering and operations teams. - Excellent problem-solving and analytical skills. - Strong communication and interpersonal skills. - Understanding of data privacy, security, and ethical considerations. - Track record of innovation and staying updated with AI research and advancements.,

About the role: This is a unique opportunity to join our fast-growing Data Science team. In the role of Data Scientist in Client Retention Analytics team, you will execute large scale, high impact data modeling projects with responsibility for designing, developing, validating, socializing, operationalizing, and maintaining data-driven analytics that provide business insights to increase operational efficiency and customer value. This person will have a flair of innovation along with a strong exposure to NLP, Classical ML, Python, statistical principles and their application in building model. What You Will Do: Deliver ad hoc modeling and advanced analytical insights to drive strategic and operational decision-making across the organization Lead all phases of the DS project lifecycle, including: understanding complex business challenges, proposing and architecting technical solutions, data wrangling, data cleaning, exploratory data analysis, feature engineering, model selection and development, rigorous model validation, operationalization, and deployment of models, as well as the clear presentation and documentation of results and actionable insights Effectively communicate complex technical solutions and analytical results to both technical and non-technical stakeholders, ensuring alignment and understanding Collaborate cross-functionally with business stakeholders, IT, and Project Management teams to design, develop, and deliver cutting-edge analytics solutions that have a measurable business impact. Leverage the latest technologies and methodologies, including Machine Learning, Artificial Intelligence, Natural Language Processing (NLP), and advanced Statistical Modeling, to solve challenging business problems Integrate advanced NLP techniques such as vector databases (VectorDB), embeddings, topic modeling, and fine-tuning of transformer models like BERT to enhance text analytics capabilities What You Will Need: Candidates with 3-6 years of professional Data Science experience must hold a Bachelors or Masters degree in Statistics, Data Science, Computer Science, or a related field Deep understanding of statistical principles and their practical application in data modeling and analysis Proven experience developing and deploying descriptive, predictive, and prescriptive models Advanced knowledge and practical expertise in NLP, including experience with vector databases, embeddings, topic modeling, and fine-tuning transformer-based models such as BERT Experience with using GenAI models (GPT4 etc.) is good to have (not must have) Proficiency in Python, SQL, and Spark; working knowledge of Power BI, Excel, and PowerPoint Hands-on experience with a variety of modeling techniques, including but not limited to: Time Series Analysis, Random Forests, Clustering, Neural Networks, Generalized Linear Models, Optimization, Design of Experiments (DOE), and Dimensionality Reduction Experience in key business applications such as churn analysis, customer profiling, and recommendation systems Ability to thrive in a fast-paced environment, managing multiple priorities and delivering high-quality results within established timelines Exceptional communication skills, with the ability to convey complex technical concepts to diverse audiences and influence key stakeholders and leaders across the organization What you will get: Competitive salary, generous paid time off policy, charity match program, Group Medical Insurance, Parental Leave, Employee Assistance Program (EAP) and more! Collaborative, team-oriented culture that embraces diversity Professional development and unlimited growth opportunities

As an AI/ML Developer, you will be responsible for utilizing programming languages such as Python for AI/ML development. Your proficiency in libraries like NumPy, Pandas for data manipulation, Matplotlib, Seaborn, Plotly for data visualization, and Scikit-learn for classical ML algorithms will be crucial. Familiarity with R, Java, or C++ is a plus, especially for performance-critical applications. Your role will involve building models using Machine Learning & Deep Learning Frameworks such as TensorFlow and Keras for deep learning, PyTorch for research-grade and production-ready models, and XGBoost, LightGBM, or CatBoost for gradient boosting. Understanding model training, validation, hyperparameter tuning, and evaluation metrics like ROC-AUC, F1-score, precision/recall will be essential. In the field of Natural Language Processing (NLP), you will work with text preprocessing techniques like tokenization, stemming, lemmatization, vectorization techniques such as TF-IDF, Word2Vec, GloVe, and Transformer-based models like BERT, GPT, T5 using Hugging Face Transformers. Experience with text classification, named entity recognition (NER), question answering, or chatbot development will be required. For Computer Vision (CV), your experience with image classification, object detection, segmentation, and libraries like OpenCV, Pillow, and Albumentations will be utilized. Proficiency in pretrained models (e.g., ResNet, YOLO, EfficientNet) and transfer learning is expected. You will also handle Data Engineering & Pipelines by building and managing data ingestion and preprocessing pipelines using tools like Apache Airflow, Luigi, Pandas, Dask. Experience with structured (CSV, SQL) and unstructured (text, images, audio) data will be beneficial. Furthermore, your role will involve Model Deployment & MLOps where you will deploy models as REST APIs using Flask, FastAPI, or Django, batch jobs, or real-time inference services. Familiarity with Docker for containerization, Kubernetes for orchestration, and MLflow, Kubeflow, or SageMaker for model tracking and lifecycle management will be necessary. In addition, your hands-on experience with at least one cloud provider such as AWS (S3, EC2, SageMaker, Lambda), Google Cloud (Vertex AI, BigQuery, Cloud Functions), or Azure (Machine Learning Studio, Blob Storage) will be required. Understanding cloud storage, compute services, and cost optimization is essential. Your proficiency in SQL for querying relational databases (e.g., PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, Cassandra), and familiarity with big data tools like Apache Spark, Hadoop, or Databricks will be valuable. Experience with Git and platforms like GitHub, GitLab, or Bitbucket will be essential for Version Control & Collaboration. Familiarity with Agile/Scrum methodologies and tools like JIRA, Trello, or Asana will also be beneficial. Moreover, you will be responsible for writing unit tests and integration tests for ML code and using tools like pytest, unittest, and debuggers to ensure the quality of the code. This position is Full-time and Permanent with benefits including Provident Fund and Work from home option. The work location is in person.,

Data Scientist with Python Job Location: Bangalore Work Experience: 2-10 years of professional experience in Data science role. Primary Skills : Python AI, ML, NLP, LLM, Neural Network Education Qualification: BE/Btech (Full time) Drive AI first solution and bring out industry leading cutting-edge AI solutions Provide an end-to-end AI based solution that excels in real client use-cases around Information Extraction Collaborate with cross functional teams (Product and Solution teams) and ensure that the AI solution is comprehensive as required by the use case Abreast with latest trends in AI technologies and provide technical leadership to execute large-scale, complex search solutions Help attract and recruit technical talent in the domain of Information Extraction Must-Have: Bachelors degree in computer science, Computer Engineering, or a related technical discipline. 2-10 years of software development experience with creating AI solutions High proficiency and experience in ML, NLP/NLU, Computer Vision, Narrow LM (BERT), General LLM, Gen AI Good hold over unsupervised learning, supervised learning, reinforcement learning and generative models Advanced knowledge of the HuggingFace (transformers, tokenizers, accelerate) and Langchain libraries Build, versioning and maintaining AI models along with performance optimizations to run at scale Create and maintain training data from large knowledge bases consisting of semantic relationships Experience with other NLP libraries like nltk, spacy, genism, etc Expertise in programming languages commonly used in AI development, such as Python and proficiency in libraries like NumPy and Pandas. Preferred: We need technical depth and an appreciation of business imperatives, we want to use technology to solve real-world problems, not indulge in over-engineering Experience with multilingual NLP A willingness to dive deep, experiment rapidly and get things done. Exceptional customer relationship skills including the ability to understand common technical requirements from multiple feature requests and lead engineering efforts to meet timelines with optimal solutions. Experience with Agile/Lean (Kanban, SCRUM), http / REST services, Linux. Proven experience mentoring and training the engineering community on complex technical issues. Disclaimer: Edgeverve Systems does not engage with external manpower agencies or charge any fees from candidates for recruitment. Show more Show less

We are seeking a skilled Python AI/ML Data Science Developer to become part of our vibrant team. If you have practical experience in training AI models, creating Python scripts for AI-driven solutions, and streamlining workflows through tools like n8n, we invite you to join us. Your enthusiasm for AI, data science, and automation would be a valuable addition to our team. Your duties will include leveraging existing datasets to train AI models with advanced machine learning algorithms and frameworks like TensorFlow, Keras, PyTorch, or scikit-learn. You will concentrate on training models using multilingual datasets that include languages such as Hindi, English, and Hinglish. Additionally, you will be responsible for developing, optimizing, and managing efficient Python scripts for various data science tasks, like data preprocessing, model training, evaluation, and automation. You will process and analyze extensive datasets to extract valuable insights that can enhance model performance and drive predictive analytics. Furthermore, you will use n8n to automate data pipelines and workflows, facilitating the integration of multiple services and enhancing operational efficiency. You will also assist in deploying AI models into production environments, monitoring their performance, and ensuring smooth operation, particularly when handling multilingual datasets. Collaboration with data scientists, engineers, and cross-functional teams will be crucial to creating AI-driven solutions that align with business goals. It is essential to stay updated on the latest AI/ML trends, tools, and technologies to implement new techniques and enhance models and scripts continually. Expertise in Hugging Face's open-source pre-trained models, such as BERT, multilingual MPNet, and DistilBERT, will be necessary to address a variety of language processing challenges. You will work on advanced AI models supporting OCR, transcription, translation, transliteration, and video contextual understanding for diverse business applications. The ideal candidate will have up to 3 years of experience as an AI/ML Developer or Data Scientist, with a strong command of Python libraries like TensorFlow, Keras, scikit-learn, Pandas, NumPy, etc. Proficiency in machine learning techniques, data wrangling, feature engineering, and model evaluation is essential. Knowledge of n8n for workflow automation, managing MCP servers, problem-solving abilities, and effective communication skills are also required. Experience with cloud-based AI/ML services, version control tools like Git, and basic understanding of Docker and containerization for model deployment are additional qualifications we seek. In return, we offer opportunities for continuous learning and growth, a competitive salary, and benefits. If you are excited about working in a collaborative and innovative environment, we would be thrilled to have you on board.,

JOB DESCRIPTION Roles & responsibilities Here are some of the key responsibilities of Sr AI Research Scientist: Research and Development: Conduct original research on generative AI models, focusing on model architecture, training methodologies, fine-tuning techniques, and evaluation strategies. Maintain a strong publication record in top-tier conferences and journals, showcasing contributions to the fields of Natural Language Processing (NLP), Deep Learning (DL), and Machine Learning (ML). Experience with POCs on emerging and latest innovation in AI. Multimodal Development: Design and experiment with multimodal generative models that integrate various data types, including text, images, and other modalities to enhance AI capabilities. Agentic AI Systems: Develop and design autonomous AI systems that exhibit agentic behavior, capable of making independent decisions and adapting to dynamic environments. Design and Implementation: Lead the design, development, and implementation of generative AI models and systems, ensuring a deep understanding of the domain. Select suitable models, train them on large datasets, fine-tune hyperparameters, and optimize overall performance. Algorithm Optimization: Optimize generative AI algorithms to enhance their efficiency, scalability, and computational performance through techniques such as parallelization, distributed computing, and hardware acceleration, maximizing the capabilities of modern computing architectures. Data Preprocessing and Feature Engineering: Manage large datasets by performing data preprocessing and feature engineering to extract critical information for generative AI models. This includes tasks such as data cleaning, normalization, dimensionality reduction, and feature selection. Model Evaluation and Validation: Evaluate the performance of generative AI models using relevant metrics and validation techniques. Conduct experiments, analyze results, and iteratively refine models to meet desired performance benchmarks. Technical Leadership: Provide technical leadership and mentorship to junior team members, guiding their development in generative AI through work reviews, skill-building, and knowledge sharing. Ability to drive multiple teams and cross-collaborate to ensure the quality delivery. Documentation and Reporting: Document research findings, model architectures, methodologies, and experimental results thoroughly. Prepare technical reports, presentations, and whitepapers to effectively communicate insights and findings to stakeholders. Continuous Learning and Innovation: Stay abreast of the latest advancements in generative AI by reading research papers, attending conferences, and engaging with relevant communities. Foster a culture of learning and innovation within the team to drive continuous improvement. Mandatory technical & functional skills Machine learning frameworks - PyTorch or TensorFlow. Deep Learning algorithms - CNN, RNN, LSTM, Transformers LLMs ( BERT, GPT, etc.) and NLP algorithms. Design experience for fine Tuning of Open source LLMs from Huggingface, Meta- LLaMA 3.1, BLOOM, Mistral AI etc. GCP : Vertex AI or Azure : AI Foundry or AWS SageMaker Scientific understanding - PEFT - LORA, QLORA, etc. Exposure to GCP : Vertex AI or Azure : AI Foundry or AWS SageMaker In-depth conceptual understanding on emerging and latest innovation in AI. Stay current with AI trends - MCP, A2A protocol, ACP, etc. Preferred Technical & Functional Skills Langgraph/CrewAI/Autogen Large scale deployment of GenAI/DL/ML projects, with good understanding of MLOps /LLM Ops Ensure scalability and efficiency, handle data tasks, Cloud computing experience- Azure/AWS/GCP BigQuery/Synapse Key behavioral attributes/requirements Ability to mentor Managers and Tech Leads Ability to own project deliverables, not just individual tasks Understand business objectives and functions to support data needs RESPONSIBILITIES Roles & responsibilities Here are some of the key responsibilities of Sr AI Research Scientist: Research and Development: Conduct original research on generative AI models, focusing on model architecture, training methodologies, fine-tuning techniques, and evaluation strategies. Maintain a strong publication record in top-tier conferences and journals, showcasing contributions to the fields of Natural Language Processing (NLP), Deep Learning (DL), and Machine Learning (ML). Experience with POCs on emerging and latest innovation in AI. Multimodal Development: Design and experiment with multimodal generative models that integrate various data types, including text, images, and other modalities to enhance AI capabilities. Agentic AI Systems: Develop and design autonomous AI systems that exhibit agentic behavior, capable of making independent decisions and adapting to dynamic environments. Design and Implementation: Lead the design, development, and implementation of generative AI models and systems, ensuring a deep understanding of the domain. Select suitable models, train them on large datasets, fine-tune hyperparameters, and optimize overall performance. Algorithm Optimization: Optimize generative AI algorithms to enhance their efficiency, scalability, and computational performance through techniques such as parallelization, distributed computing, and hardware acceleration, maximizing the capabilities of modern computing architectures. Data Preprocessing and Feature Engineering: Manage large datasets by performing data preprocessing and feature engineering to extract critical information for generative AI models. This includes tasks such as data cleaning, normalization, dimensionality reduction, and feature selection. Model Evaluation and Validation: Evaluate the performance of generative AI models using relevant metrics and validation techniques. Conduct experiments, analyze results, and iteratively refine models to meet desired performance benchmarks. Technical Leadership: Provide technical leadership and mentorship to junior team members, guiding their development in generative AI through work reviews, skill-building, and knowledge sharing. Ability to drive multiple teams and cross-collaborate to ensure the quality delivery. Documentation and Reporting: Document research findings, model architectures, methodologies, and experimental results thoroughly. Prepare technical reports, presentations, and whitepapers to effectively communicate insights and findings to stakeholders. Continuous Learning and Innovation: Stay abreast of the latest advancements in generative AI by reading research papers, attending conferences, and engaging with relevant communities. Foster a culture of learning and innovation within the team to drive continuous improvement. Mandatory technical & functional skills Machine learning frameworks - PyTorch or TensorFlow. Deep Learning algorithms - CNN, RNN, LSTM, Transformers LLMs ( BERT, GPT, etc.) and NLP algorithms. Design experience for fine Tuning of Open source LLMs from Huggingface, Meta- LLaMA 3.1, BLOOM, Mistral AI etc. GCP : Vertex AI or Azure : AI Foundry or AWS SageMaker Scientific understanding - PEFT - LORA, QLORA, etc. Exposure to GCP : Vertex AI or Azure : AI Foundry or AWS SageMaker In-depth conceptual understanding on emerging and latest innovation in AI. Stay current with AI trends - MCP, A2A protocol, ACP, etc. Preferred Technical & Functional Skills Langgraph/CrewAI/Autogen Large scale deployment of GenAI/DL/ML projects, with good understanding of MLOps /LLM Ops Ensure scalability and efficiency, handle data tasks, Cloud computing experience- Azure/AWS/GCP BigQuery/Synapse Key behavioral attributes/requirements Ability to mentor Managers and Tech Leads Ability to own project deliverables, not just individual tasks Understand business objectives and functions to support data needs QUALIFICATIONS This role is for you if you have the below Educational Qualifications Masters (MS by Research)/PhD or equivalent degree in Computer Science Preferences to research scholars from Tier 1 colleges- IITs, NITs, IISc, IIITs, ISIs, etc. Work Experience 12+ Years of experience with strong record of publications (at least 5) in top tier conferences and journals #KGS Show more Show less

About Info Edge: InfoEdge's mission is to create world-class platforms that transform lives by continuously innovating. Our products and services are built keeping our customers in mind. We always delight our customers by delivering superior value through enhanced offerings on the internet and other platforms. Through our continuous investment across various businesses, especially in cutting-edge technology, machine learning and artificial intelligence (AI), we have built a robust system that constantly increases our predictive powers on customer behaviour, and optimizes and improves our systems. Our various teams tirelessly work together to solve problems, innovate, and create something to empower our customers. At Info Edge, people are our core competitive advantage and we will continue doing all that is needed to attract and retain the best available talent. * About BU: Corporate Function * Required Educational Qualification: PhD/ MTech / BTech with relevant experience from Tier 1 Campus only. * Desired Experience: 0 - 5 Years * Job Objective: You will be building innovative Machine Learning solutions for vital and complex business problems. *Fill this form to proceed further: ( https://tinyurl.com/FAIscientist ) Job Description: As AI Scientist you will: Develop algorithms and build systems to extract seemingly unseen trends and information from user content such as resumes, job description and profile information available through various sources and in different modalities such as numeric, structure and unstructured texts and images. Identify potential new business problems that can be solved through machine learning. Ideate, formulate, create metrics and execute on such problems and get buy in from business. Identify potential data-driven machine learning solutions to improve user experience through personalization and prediction of user preferences. Build intelligent systems to capture and model the vast amount of behavior data to enrich the content understanding with behavioral information. Identify the appropriate and cutting edge machine learning tools for various supervised and unsupervised tasks in the NLP, deep learning, semantic search, LTR space for building highly accurate and scalable recommendation systems and information retrieval solutions. Design solutions for scalable and real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance. Participate in external forums /discussions, publish research papers, keep up-to-date on latest publications and build external/internal networks. Required Skills: Strong fundamental understanding and research experience in machine learning/Deep Learning/NLP/Information Retrieval/Artificial Intelligence areas. Strong applied knowledge of machine learning in solving real-world business problems with a significantly broad number of algorithms covering the landscape of classification, regression; discriminative, generative; supervised, unsupervised, semi-supervised; linear and non-linear dimensionality reduction, feature-extraction, feature selection, feature-learning. Industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems. An excellent problem solving skills with a research oriented approach. Ability to capture, manage, create pipelines and process Big Data. Desired Skills: Ability to understand Business challenges and define solutions aligned to the needs.

Job Description At American Express, our culture is built on a 175-year history of innovation, shared and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. How will you make an impact in this role Function Description: With a focus on digitization, innovation, and analytics, the Global Decision Sciences (GDS) team creates central, scalable platforms and customer experiences to help markets across all of these priorities. Charter is to drive scale for the business, and accelerate innovation for both immediate impact as well as long-term transformation of our business. A unique aspect of GDS is the integration of diverse skills across all of its remit. GDS has a very broad range of responsibilities, resulting in a broad range of initiatives around the world. The Amex AI Labs of American Express Corporation is looking for best in class Senior Research Engineers to work in a dynamic and rewarding workplace. Amex AI Labs is currently co-located in Bangalore, Gurgaon and New York and involves dynamic and talented researchers with Ph.D. or Master's degree from top tier institutes in India and abroad having research and product development expertise in AI/ML technologies such as - Deep Learning, Data Science, Natural Language Processing, Cloud Technologies and related technical areas. Going beyond building products and solutions for traditional financial domains such as credit and fraud, the team is also working on challenging research problems in domains such as services, human resource management, travel & lifestyle, and many more. The key goal is to progress the state of the art in science and develop products to solve business problems, in a domain-agnostic manner, for American Express. Purpose of the Role: Collaborate on next generation research services in the areas of Artificial Intelligence (AI) to aid solutions to complex business problems for American Express Responsibilities: Amex AI Labs is looking for individuals with AI R&D background for AI Research & Services team in Bangalore/Gurgaon. The team works on handling capabilities centred on Document Analysis, NLP, AI research from conception to launch. Successful candidates are expected to partner with different business and technology teams in American Express to build capabilities for high impact use-cases. We are looking for extremely agile and entrepreneurial candidates who will help innovate and execute product initiatives across the company. . Lead the ideation and launch of innovative AI/ML capabilities & services . Hands on Deep learning Algorithms like BERT, RNN, LSTM, Transformer, GRU, GAN etc . Understanding Generative AI based closed source models like ChatGPT, Claude, Llama for different usecases . Fine Tuning open source models like Llama and other models on domain specific data . Working with MLOPs capability like MLFlow, AirFlow etc and understanding of deployment capabilities on public cloud (AWS, GCP) and on-prem infrastructure . Technically hands-on working with big data sets using Python/JAVA/SPARK, doing EDA and bringing insights from data . Building POCs basis on research papers analysis while simulating business impact and Transform MVPs to production grade capabilities in collaboration with engineering teams . Authoring and publishing papers, adopting open source tools, presenting in conferences, conducting R&D driving company revenue. . Innovate ways to evangelize the product to drive Amex wide user adoption . Contribute to the strategy and roadmap of AI/ML Initiatives to help drive most impact . Evaluate prospective features in AI Services and ability to prioritise them with changing requirements in the direction of AI adoptions. Leadership Outcomes: . Lead with an external perspective, challenge status quo and bring continuous innovation to our existing offerings . Demonstrate learning agility, make decisions quickly and with the highest level of integrity . Lead with a digital mindset and deliver the world's best customer experiences every day Minimum Qualifications Strong Internal Candidate Preferred . 5+ years of building machine learning models using advance AI techniques 4-5 years of experience in working with product/engineering/automation development teams in a fast paced, complex, and dynamic environment. . Experience in leveraging Agile, Scrum or other rapid application development methodologies Undergraduate/Master's/PHD in Computer Science/ Data Science/ Statistics/ Mathematics, MBA from institutes of global repute. Preferred Qualifications Technical Skills: 1. Good coding skills in Python, SPARK, Hive, GIT, API 2. Good Understand of Deep Learning Algorithms 3. Superior math & programming skills and hands-on experience in machine learning tools 4. Understanding of how CI/CD works 5. Exposure to Public Cloud Deployment (AWS, GCP) 6. Proficient in statistical techniques 7. Background in Natural Language Processing - with hands on experience in frameworks like langraph, langchain, vector databases, Agentic frameworks Behavioral Areas: Enterprise Leadership Behaviors . Set The Agenda: Put Enterprise Thinking First, Lead with an External Perspective . Bring Others With You: Build the Best Team, Seek & Provide Coaching Feedback, Make Collaboration Essential . Do It The Right Way: Communicate Frequently, Candidly & Clearly, Make Decisions Quickly & Effectively, Live the Blue Box Values, Great Leadership Demands Courage We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

About the Team The Panacea team has a passionate set of engineers across India and US office. We move fast, collaborate closely, and care deeply about quality and ownership. Our mission is to deliver AI/ML-powered developer productivity tools that solve real engineering and support pain points at scale. Why Join Us Build AI-first observability tools that redefine how engineers triage and troubleshoot. Own systems that reduce hours of manual work in engineering and SRE workflows . Collaborate with a tight-knit team of high-ownership engineers who are passionate about impact and innovation. Hybrid work model that supports flexibility and deep focus. Help shape the central AI charter at Nutanix and influence future AI products across the company. Your Role AI-Powered Observability Platform : Own the vision, architecture, and delivery of Panaceas ML-based log and metrics analyzer that reduces triage time and improves engineering efficiency. AI/ML-powered Log Analyzer Tool : Use deep learning (e.g., ModernBERT ) to represent log messages, detect anomalies, group patterns, and surface actionable insights to users. Metrics Anomaly Detection Engine : Build robust ML models to detect anomalies in time-series metrics like CPU, memory, disk I/O, network traffic, service health , and moreautomatically identifying performance degradation or system regressions across distributed environments. Auto-RCA Engine : Combine log and metrics signals with graph-based correlation and LLM-powered summarization to automatically diagnose the root cause of system failures. Feedback Loop & Continuous Learning : Build infrastructure for incorporating user feedback to continuously retrain and improve anomaly detection systems. LLM Integration : Integrate LLMs for user queries, problem summarization, anomaly explanation, and contextual recommendations. Central AI Charter : Contribute to Nutanixs foundational AI platform by defining shared tooling, datasets, governance, and reusable ML components across products. Responsibilities Architect and scale ML pipelines for real-time and batch-based anomaly detection in both logs and time-series metrics. Build and fine-tune ModernBERT and other transformer-based models for log understanding, anomaly classification, and summarization. Develop unsupervised and semi-supervised ML models for detecting anomalies in system metrics (CPU, memory, network throughput, latency, etc.). Implement correlation models to connect anomalies across logs and metrics to form a cohesive RCA narrative. Own the entire ML lifecycle: data ingestion, feature extraction, model training, evaluation, deployment, and monitoring. Build explainable AI systems that increase adoption and trust within engineering, QA, and support teams. Collaborate with cross-functional stakeholders (SRE, QA, Dev) to deeply understand pain points and translate them into intelligent tooling. Drive technical excellence through code and design reviews, mentoring, and setting engineering best practices. What You Will Bring Educational Background : B.Tech/M.Tech in Computer Science, Machine Learning, AI, or related fields. Experience : 12+ years of engineering experience , including designing , developing and deploying AI/ML systems at scale. ML Expertise : Strong in time-series anomaly detection, statistical modeling, supervised/unsupervised learning. Experience building ML models for metrics data (CPU, memory, IOPS, network, etc.) using models like Isolation Forest, Prophet, LSTM, or deep autoencoders. Expertise in NLP using ModernBERT, BERT, or log classification, clustering, and summarization. Experience with LLMs for downstream tasks like summarization, root cause reasoning, or intelligent Q&A. Engineering Skills : Strong Python background, hands-on with ML libraries (PyTorch, TensorFlow, Scikit-learn), time-series frameworks, and MLOps tools. Familiar with data pipelines and serving models. Observability Knowledge : Hands-on with logs, metrics, traces, and popular monitoring tools (e.g., Prometheus, Grafana, ELK). Leadership : Ability to independently drive projects from requirements to delivery, mentor junior engineers, and deliver business impact.