Skills from Primary Skill Cluster Kore.AI, JavaScript, NLP Skills outside Primary Skill Cluster About The Role ::Responsibilities:Bachelor Degree with computer science or software engineering as subject or relevant degree. 4+ years of experience with software development, with expertise in developing and designing. Strong Proficiency in programming languages such as javascript. Required Skills:Experienced working with rule base chatbots and conversational AI specifically kore.ai. Experience in kore.ai developing bots , integration with api and software development kit. Solid understanding of Natural Language Processing and Machine Learning. Good problem - solving and debugging skills with keen attention to details. Familiar with agile software development method and tools Nice to have skills:Excellent verbal and written communication skills with ability to communicate complex concept to both technical and non-technical stake holders

NLP Experience:5 to 8 years of good working experience Experience with Text Classification, NER models - fine-tuning and zeroshotExperience with Huggingface, PytorchExperience with Document ProcessingPython / AI Engineering:Proficient in python - build re-usable and scalable data pipelinesNoSQL databasesData analysis and ML/DL frameworksWeb API frameworksUnit testing frameworksMicroservices / Cloud:Docker, ECS / EKSGood experience with any one cloud service provider:AWS PreferrableGeneral Requirements:Ability to handle large scale unstructured dataFlexible to learn new frameworks and keep up with latest NLP developments

Job description Experienced and skilled technical lead Architect to drive AI solutions across the organization liaising between the Product Management team and the engineering teams translating business requirements into robust scalable and innovative AI solutions Responsibilities Technical Leadership Solution Architecture Lead the design architecture and implementation of AI solutions utilizing Google Gemini Python and other relevant AI ML technologies This includes defining system architectures identifying appropriate technologies and ensuring scalability and maintainability Business Case Solutioning Collaborate closely with the Product Management team to understand business needs and translate them into feasible and impactful AI solutions This involves analyzing requirements identifying potential use cases and developing comprehensive technical solutions Technology Evaluation Selection Research evaluate and recommend the most suitable AI ML technologies and frameworks to address specific business challenges Stay abreast of the latest advancements in the AI landscape particularly concerning Google Gemini and related ecosystems Collaboration Communication Effectively communicate technical concepts to both technical and non technical audiences Collaborate effectively with cross functional teams including Product Management Engineering and Operations Documentation Knowledge Sharing Create and maintain comprehensive technical documentation including architecture diagrams design specifications and implementation details Contribute to the development of internal knowledge bases and best practices Required Skills Qualifications Extensive experience 8 years in designing, developing and deploying Analytics projects Hands on experience in building AI ML solutions Proven track record of successfully delivering complex AI projects Deep understanding of Google Geminis capabilities and limitations Experience working with Google Cloud Platform GCP and its AI ML services is highly desirable Proficiency in Python and other relevant programming languages used in AI ML development egTensorFlow PyTorch Strong expertise in various AI ML techniques including deep learning natural language processing NLP computer vision and reinforcement learning Experience with designing and implementing scalable and robust AI systems Familiarity with microservices architecture and containerization technologies e g Docker Kubernetes is a plus Excellent problem solving and analytical skills Ability to quickly understand complex business problems and translate them into technical solutions Strong communication interpersonal and collaboration skills Ability to effectively communicate technical concepts to both technical and non technical stakeholders Experience working in an Agile development environment Education in Computer Science Engineering or a related field Preferred Skills Qualifications Experience with AI ML frameworks relevant to Google Gemini Experience with data engineering frameworks and technologies Experience with MLOps and CI CD pipelines Experience with deploying AI models to production environments Prior experience working within a COE structure

Fresher or 3+ years of experience in AI/ML development with a focus on Generative AI and LLMs. Design, develop, and implement AI/ML models, including Generative AI and LLM-based solutions.

ML Engineer job profile Machine Learning is a field of artificial intelligence that focuses on developing systems that can learn and improve from experience. Machine Learning Engineers work on creating and implementing AI models and algorithms to solve complex problems. This role often involves working with large datasets, developing algorithms, and deploying models into production environments. ML Engineer job description We are seeking an enthusiastic and motivated Machine Learning Engineer with 1-3 years of experience to join our team. As a Machine Learning Engineer, you will be responsible for designing, building, and maintaining machine learning models with a focus on Generative AI, Large Language Models (LLMs), and Natural Language Processing (NLP). You will use your skills and knowledge to tackle real-world challenges and contribute to the advancement of AI technology. ML Engineer duties and responsibilities Design, develop, and implement efficient and scalable machine learning models and algorithms Work closely with software engineers to integrate ML models into production systems Implement and optimize NLP algorithms and pipelines Optimize and fine-tune existing models for improved performance Contribute to the research and implementation of state-of-the-art GenAI techniques Participate in the full machine learning lifecycle, from data preparation to model deployment Collaborate with cross-functional teams to identify and solve complex business problems using AI Stay up-to-date with the latest advancements in ML, especially in GenAI, LLMs, and NLP Document your work, including model architectures, experiments, and results Must have skills C++ Programming: Proficiency in writing efficient, modular, and maintainable C++ code, including knowledge of advanced features such as templates, STL, and memory management, and implementation of data structures, algorithms, object-oriented programming principles, and design Visual Studio: Experience using Visual Studio IDE for C++ development, including project management, debugging, and performance profiling. VC++ : Background in Visual C++, including building applications for Windows platforms, integrating with Windows APIs, etc Database Management: Experience working with relational databases (e.g., SQL Server, MySQL) and proficiency in writing efficient SQL queries, database design, and optimization. Good to have skills File System Knowledge: Understanding of different file systems such as FAT (File Allocation Table), APFS (Apple File System), and NTFS (New Technology File System), and their structures, features, and limitations. Low-Level APIs: Familiarity with low-level APIs for system-level programming, including filesystem APIs, device drivers, and system calls. Understanding of memory management, I/O operations, and concurrency control at a low level.

Key Responsibilities: Design & Develop AI Models : Create and implement machine learning models and algorithms to solve business challenges. Data Processing & Analysis : Analyze large datasets, preprocess data, and apply statistical techniques to improve model accuracy. Deep Learning & NLP : Work with advanced AI techniques such as neural networks, reinforcement learning, and natural language processing to build intelligent systems. Model Optimization : Optimize models for performance, scalability, and efficiency using techniques such as hyperparameter tuning and model deployment. Collaboration : Collaborate with software engineers, data scientists, and business teams to integrate AI solutions into applications and platforms. Testing & Validation : Test and validate AI models, ensuring their effectiveness, and continuously improve them based on feedback and new data. Documentation : Write clear documentation for models, algorithms, and code to ensure maintainability and scalability. Research : Stay updated with the latest advancements in AI technologies and research to apply cutting-edge techniques. Required Skills and Experience: Model Hosting and Deployment: Strong experience with deploying and managing machine learning models in production environments. Server Infrastructure: Proficient in building and managing servers to host and serve models for scalable access. APIs: Expertise in developing and deploying RESTful APIs for model inference. Redis & Celery: Solid experience with Redis for caching and Celery for task management and background job processing. PostgreSQL: Strong knowledge of PostgreSQL for data management and querying in the context of ML applications. Model Repositories: Experience with version control and repositories for machine learning models, including integration with Git or similar platforms. Cloud Platforms: Experience with cloud services (e.g., AWS, GCP, Azure) for deploying and managing models at scale. Preferred Skills: Familiar with CI/CD pipelines for AI models to ensure automated testing, deployment, and updates. Experience with containerization technologies such as Docker and Kubernetes for deployment and orchestration. Familiarity with frameworks like TensorFlow Serving, TorchServe, or similar for serving models in production. Knowledge of model monitoring tools and logging frameworks. Ability to work in a fast-paced, collaborative environment with cross-functional teams. Knowledge in consumer and server grade GPU to handle CUDA compatability issues.

Job Description- Data Scientist Job Summary : As a Data Scientist, you'll design, develop, and deploy natural language processing models to drive business value. You'll collaborate with cross-functional teams to identify opportunities, collect and pre-process data, and implement scalable NLP solutions. Responsibilities : 1. Develop and fine-tune Transformer models (e.g., BERT, RoBERTa, XLNet) for NLP tasks (e.g., text classification, sentiment analysis, named entity recognition) 2. Collect, pre-process, and annotate datasets for NLP model training 3. Conduct research and stay up-to-date with advancements in Transformer architectures and NLP 4. Develop and fine-tune conversational AI models (e.g., intent recognition, sentiment analysis, dialogue management) Requirements : 3+ years of experience in NLP, machine learning, and data science Master's or Ph.D. in Computer Science/Data Science (Preferable) Experience with deep learning frameworks Clarity on fundamentals of NLP and ML algorithms Excellent problem-solving and communication skills What We Offer : Competitive salary and benefits package. Opportunities for professional growth and development. Collaborative and dynamic work environment.

Role & responsibilities Require AI prompt / Python engineer with Open AI experience, LLM, RAG, Langchain. Experience in ML/DL. Overall Experience 8+ years Preferred candidate profile Perks and benefits

Job Description Role & Responsibilities: Develop and deploy Generative AI solutions using LLMs and related technologies. Fine-tune large language models (LLM fine-tuning) to improve performance. Work on Retrieval-Augmented Generation (RAG) methodologies to optimize AI outputs. Implement Prompt Engineering techniques for effective model interaction. Utilize Python, TensorFlow, and PyTorch for AI model development and optimization. Work with cloud platforms like Azure, AWS, or GCP to deploy and scale AI models. Collaborate with cross-functional teams to integrate AI solutions into business applications. Maintain AI/ML pipelines and workflows using LLMOps best practices. Preferred Candidate Profile: 5 to 8 years of experience in AI, ML, or Data Science roles. 2 to 3 years of experience specifically in GenAI solution development, LLM fine-tuning, RAG, or LLMOps. Strong background in Natural Language Processing (NLP) and Transformer models. Hands-on experience with cloud-based AI solutions (Azure, AWS, GCP). Excellent problem-solving skills and ability to work in a fast-paced environment. Perks and Benefits: Competitive salary and performance-based incentives. Work with cutting-edge AI technologies and industry leaders. Opportunities for career growth and learning. Health insurance and other standard benefits.

Some of the key responsibilities include: Data mining involves extracting usable data from valuable sources. Possesses extensive knowledge of Python, including a deep understanding of machine learning libraries. Utilises machine learning tools to select features, create and optimise classifiers, and carry out preprocessing of both structured and unstructured data. Proficient with deep learning models such as ANN, CNN, and NLP. Enhances data collection procedures to encompass all relevant information for developing analytical systems. Processes, cleanses, and validates the integrity of data for analysis. Analyses large volumes of information to identify patterns and solutions. Develops prediction systems and machine learning algorithms. Proposes solutions and strategies to address business challenges. Collaborates with business and IT teams. Required Technical Skills: Programming Skills Knowledge of statistical programming languages such as R and Python, along with database query languages like SQL, is desirable. Statistics Strong applied statistical skills, encompassing knowledge of statistical tests, distributions, regression, and maximum likelihood estimators, are essential for data-driven companies. Machine Learning A good understanding of machine learning methods is required. Strong Math Skills (Multivariable Calculus and Linear Algebra) - Understanding the fundamentals of Multivariable Calculus and Linear Algebra is crucial, as they form the basis of many predictive performance and algorithm optimization techniques. Data Wrangling Proficiency in managing data imperfections is a key aspect of a data scientist's job description. Experience with Data Visualisation Tools such as Matplotlib, which assist in visually encoding data. Required Skills: Good with ML, Computer Vision & DL concepts Strong experience in creating data pipelines Proficiency in database management Hands-on expertise in model retraining and deployment Proficiency in Python coding Cloud AWS/Azure Looking for 6+Yrs of experience. Looking for Immediate to 30 Days of Notice Period (Also Serving NP Professionals)

We are seeking an enthusiastic Python Developer with expertise in Azure, Data Science, Natural Language Processing (NLP), and experience working with Streamlit, Gradio, and Flask. As a Python Developer at our company, you will be involved in building cutting-edge applications, leveraging large language models, and deploying solutions using Azure cloud technologies. If you are passionate about pushing the boundaries of AI-driven applications and have hands-on experience with Streamlit, Gradio, Flask, and Hugging Face's large language models, we would love to have you join our team. Responsibilities: 1. Collaborate with cross-functional teams to understand business requirements and design software solutions. 2. Develop and deploy Python-based applications using Streamlit, Gradio, and Flask frameworks for interactive data visualization and AI-powered interfaces. 3. Utilize Azure cloud services for seamless deployment, scaling, and management of applications. 4. Apply data science and NLP techniques to implement advanced analytics and machine learning algorithms. 5. Integrate and fine-tune large language models from Hugging Face, tailoring them to specific use cases. 6. Explore and experiment with state-of-the-art NLP models to improve application performance. 7. Work with large datasets and implement data preprocessing, cleaning, and transformation pipelines. 8. Optimize application performance, responsiveness, and scalability for large user bases. 9. Collaborate with data scientists to implement and integrate NLP-driven solutions into existing applications. 10. Ensure the security and privacy of data throughout the development process. 11. Conduct code reviews and adhere to best practices for code quality and maintainability. 12. Stay updated on the latest advancements in NLP, data science, and cloud technologies.

Job Profile Summary Quantitative Analytics: Covers jobs responsible for utilizing advanced mathematical skills, such as probability, statistics, and machine learning, to construct, design, develop, validate, and implement highly complex quantitative and predictive analytic models that offer continuous insights to a wide range of products, business, or risk mitigation initiatives. About this role: Wells Fargo is seeking a Senior Quantitative Analytics Specialist Internal Audit. Seeking an Internal Audit Artificial Intelligence (AI) and Machine Learning (ML) Model Development Center of Excellence group (IA MD COE). The IA MD COE team in Internal Audit is responsible for developing and deploying NLP, machine learning, and AI solutions for key strategic Audit initiatives such as risk management and compliance, business operational excellence, and team member experience. The team is looking for experienced analytics professional to add to its AI/ML/NLP model development team. As part of the IA MD COE data science team, you will be responsible for designing, developing, and implementing AI/ML NLP models for Internal Audit. You will be leveraging unstructured text such as emails, text messages, notes, and semi-structured data in combination of structured data to apply text analytics and AI/NLP/ML techniques. You will use open stack programming languages (primarily Python) and/or vendor solutions to develop models and deploy them on Wells Fargos AI platform. In this role, you will: Perform highly complex activities related to creation, implementation, and documentation Use highly complex statistical theory to quantify, analyze and manage markets Forecast losses and compute capital requirements providing insights, regarding a wide array of business initiatives. Utilize structured securities and provide expertise on theory and mathematics behind the data. Manage market, credit, and operational risks to forecast losses and compute capital requirements Participate in the discussion related to analytical strategies, modeling and forecasting methods. Identify structure to influence global assessments, inclusive of technical, audit and market perspectives. Collaborate and consult with regulators, auditors and individuals that are technically oriented and have excellent communication skills Required Qualifications: 4+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science About this role: The ideal candidate should be able to think outside the box to uncover new ways to analyze unstructured data in conjunction with analytical tools to answer complicated business questions. As part of the model development team, you will be responsible of delivering solutions that meet business needs as well as any efforts related to model documentation and reviews to ensure the modeling processes and procedures meet corporate model risk policies and requirements. Universe and Technology Solutions - Audit Universe, AE Risk Assessments, Change Management Risk Management, AMS, SharePoint, Shared Drives, Data Management, and other technology Innovation - Artificial Intelligence, Machine Learning, Advanced Analytics, Automation, Models, Audit Reporting, LOB Innovation, Operational Innovation Professional Practices - Plan & Issue Management, Practices, Audit Policy Library, oversight of Audit's issue management and remediation activities, Validation Review Committee Employee Operations - Employee Experience, and Resource Acquisition, Management, & Reporting Quality Assurance (QA) - Assess and drive continuous improvement in the quality of Audit execution, QA reviews, aggregation of QA issues, QA reporting, validation of corrective actions, credible challenge, continuous improvement. Practices supports the entire audit department, providing the framework and methodology, control functions, and overall operational support for employees. Practices looks to continuously enhance processes and policies to ensure Audit is efficient and effective in reaching its goals. The Innovation team includes analytics professionals focused on building advanced solutions for the department - such as artificial intelligence, machine learning, advanced analytics, and automation. This is accomplished through strong partnerships with the audit teams Practices supports. Desired Qualifications: Internal Audit experience Generative AI and Large Language Model experience Ability to work and influence successfully within a matrix environment and build effective business partnerships with all levels of team members Good analytical skills with high attention to detail and accuracy GitHub experience Experience with search engine libraries, such as, but not limited to Stanford NLP Library or Lucene search engine Job Expectations: Develop, implement, and calibrate various analytical models Perform highly complex activities related to financial products, business analysis and modeling Perform basic statistical and mathematical models using Python, R, SAS, C++ and SQL Perform analytical support and provide insights regarding a wide array of business initiatives Provide solutions to business needs and analyze work flow processes to make recommendations for process improvement in risk management Collaborate and consult with peers, colleagues, managers and regulators to resolve issues and achieve goals Design, develop, and deploy AI/ML models using state of the art NLP and ML techniques available in the open stack and/or vendor solutions Data visualization Communicating the results Responsible of model development document and monitoring processes Adhere to corporate model risk policy and ensure compliance with model risk management Working with other data science teams to identify, gather, retain, and publicize modeling artifacts required for approved and repeatable processes Contribute to NLP data science teams group effort to stay concurrent with the cutting edge and bleeding edge of NLP/ML/DL algorithms, methodologies in the open source community and vendor solutions. Work with AI technology and production teams to operationalize models Ability to travel up to 10% of the time Posting End Date: 26 Feb 2025 *Job posting may come down early due to volume of applicants. We Value Diversity At Wells Fargo, we believe in diversity, equity and inclusion in the workplace; accordingly, we welcome applications for employment from all qualified candidates, regardless of race, color, gender, national origin, religion, age, sexual orientation, gender identity, gender expression, genetic information, individuals with disabilities, pregnancy, marital status, status as a protected veteran or any other status protected by applicable law. Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business units risk appetite and all risk and compliance program requirements. Candidates applying to job openings posted in US: All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic. Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process. Applicants with Disabilities To request a medical accommodation during the application or interview process, visit . Drug and Alcohol Policy Wells Fargo maintains a drug free workplace. Please see our to learn more. Wells Fargo Recruitment and Hiring Requirements: a. Third-Party recordings are prohibited unless authorized by Wells Fargo. b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.

We are looking for an immediate joiner, Lead Data Science Specialist Experience: 8+ Years Location: Bangalore/Chennai/Pune Mode of working: Hybrid Requirement: Mandatory Skills Gen AI Experience Python SQL Large language models (LLMs) and RAG architecture machine learning algorithms NLP Azure Blob storage / Azure Storage Team Handling Experience Please send your updated resume to my mail ID: priyadarshini.srinivasan@sapwood.net and also furnish the following details, Current CTC: Expected CTC: Notice Period: Thank You Regards Priyadarshini Srinivasan Senior Manager - Team & Key Accounts Sapwood Ventures Pvt. Ltd.

• Experience in machine learning, data mining and analysis for model development, validation, implementation in product integration. • Experience in large-scale data processing frameworks and technologies. • Programming languages- Python or Scala.

Job Title: NLP Engineer Job Location: Chennai / Coimbatore Experience: 2+ years Job Type: Full-Time We are seeking an exceptional Senior NLP Engineer to join our cutting-edge AI/ML team. In this role, you will leverage your deep expertise in natural language processing, large language models, and retrieval-augmented generation to develop and optimize innovative NLP applications. Responsibilities: Design, develop, and deploy state-of-the-art NLP solutions utilizing LLMs and RAG architectures. Implement and optimize vector databases for efficient retrieval and augmentation of LLM-based systems. Collaborate with cross-functional teams to identify and address complex NLP challenges. Stay at the forefront of NLP research and apply latest techniques to enhance our AI/ML applications. Mentor junior engineers and contribute to the growth and knowledge sharing within the team. Requirements: Bachelor or Masters in Computer Science, NLP, ML or related field 2+ years of experience in developing NLP applications, (expertise in LLMs and RAG would be a plus) Strong understanding of transformer architectures, few-shot learning, and prompt engineering. Hands-on experience with NLP frameworks like Hugging Face, spaCy, NLTK, AllenNLP, etc. Proficiency in Python, PyTorch, TensorFlow and familiarity with C++/CUDA for optimization Experience with vector databases like Pinecone, Weaviate, Milvus for building RAG systems. Excellent problem-solving skills and ability to design efficient, scalable NLP pipelines. Strong communication skills and ability to collaborate in a fast-paced environment. Preferred Qualifications: Experience with deploying NLP models in production using AWS, GCP or Azure Knowledge of MLOps best practices and tools like MLflow, Kubeflow, AWS SageMaker If you are passionate about pushing the boundaries of NLP and developing game-changing AI applications, we would love to hear from you. Join our world-class team and help shape the future of intelligent systems.

We are seeking a highly skilled and hands-on Cloud DevOps Engineer to join our dynamic team. The ideal candidate will have extensive experience in managing and optimizing cloud infrastructure on AWS and GCP, with a strong focus on automation and integration/continuous deployment (CI/CD) practices. Key Responsibilities: AI & NLP Experience: Experience working with LLMs (GPT, Claude, Gemini) for reasoning & information retrieval (RAG experience required) Experience with speech-to-text (Deepgram, Open AI Whisper, or similar). Experience with text-to-speech (Azure Speech, Eleven Labs, or similar) Software Development: Strong experience with Python (a sync programming, API integrations). Experience working with Vocode or similar AI voice frameworks. Knowledge of database design (PostgreSQL, MySQL, SQL Server, or NoSQL) to store claim data. API development experience Cloud & DevOps: Experience with AWS / GCP / Azure for hosting and API integrations. Troubleshooting skills for AWS services and GitLab pipelines. Qualifications: Minimum 3+ years of experience as a DevOps Engineer or similar software engineering role. Bachelors degree in Computer Science, Engineering, or a related field Working knowledge of Python, databases and SQL Experience in developing/engineering applications Strong problem-solving skills, excellent communication, and the ability to work collaboratively in a team environment.

Responsibilities Roles and Responsibilities: Experience with building AI and machine learning solutions, Machine Learning Operation frameworks such as Kubeflow, and leveraging specific machine learning architectures (e.g., deep learning, LSTM, etc.) Experience working in Gen AI Framework like Langchain Experience working in Gen AI Open-source platform like TensorFlow, Keras and PyTorch Understanding of AI Models, Large Language Models, and AI specialized infrastructure especially as it relates to AI trends and issues within businesses. Understanding of responsible AI practice. Provide AI expertise to support the technical relationship with customers, including product and solution briefings, proof-of-concept work. Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to implement a complete solution using Gen AI best practices. Support developers, creators, and enterprises to leverage Generative Language APIs so they can build their own AI products in the future. Work with the team to identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers. Strategize surrounding solution code development in collaboration with internal or external developers, users, partners, clients, or stakeholders as needed. Build APIs that cater to the diverse need of customers through REST API Strong understanding of Database concepts (Vector DBs - e.g Mongo, Chroma DB) and connectivity. Experience in AWS Sagemaker Should have background knowledge on Google Vertex and Azure AI Suite Complete understanding of LLM Models Complete understanding of Foundation Model training Experience in Airflow and DataAgent development Work experience in Kubernetes & Docker containers. Evaluation of GenAI models Technical and Professional Requirements: Primary skills: Artificial Intelligence, Machine Learning, Python, NLP, TenserFlow Preferred Skills: Technology->Big Data->Natural language processing(NLP) Technology->Artificial Intelligence->Artificial Intelligence - ALL Technology->Machine Learning->TensorFlow Technology->Machine Learning->Python Technology->Data Science->Machine Learning Additional Responsibilities: At least 5+ years of programming experience in Python and real time working experience in Gen AI Implementation experience in various Machine Learning and Deep Learning algorithms Strong proficiency in Programming Languages such as Python and R and Gen AI framework like TensorFlow and PyTorch. In depth knowledge of Machine Learning, Deep Learning architecture and Generative AI LLM models. Experience in data cleansing and processing for Machine Learning applications. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Proficiency with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. Proficiency on Prompt Engineering and responsible AI. Good Communication skills Good analytical and problem-solving skills Educational Requirements Master Of Engineering,Master Of Technology,Bachelor Of Science,Bachelor of Engineering,BCA,BTech Service Line Cloud & Infrastructure Services

Role & Responsibility: Partner with Product Managers, Engineers, and other key stakeholder to deeply understand business requirements and translate them into actionable technical roadmaps. Identify and prioritize AI use cases aligned with organizational goals, develop a scalable and sustainable implementation roadmap, and conduct ROI analysis for on-prem LLM deployments. Create sophisticated software designs driven by AI-powered experiences, performance, scalability, security, reliability, and ease of maintenance. Define and develop complex enterprise applications through AI Agentic frameworks encompassing of responsiveness, responsibility, traceability, and reasoning. Leverage modeling techniques like UML and Domain-Driven Design to visualize intricate relationships between components and ensure seamless integrations. Lead large-scale platform projects delivering No-code workflow management, HRMS, Collaboration, Search engine, Document Management and a host of services for our employees. Champion automated testing, continuous integration/delivery pipelines, MLOps and agile methodologies across multiple teams. Spearhead efforts to integrate artificial intelligence capabilities with other internal/external ecosystems to deliver seamless user experience. Skillset Required: Mandatory BTech/MTech/PhD in Computer sciences with specialization in AI/ML . Proven track record of leading large-scale digital transformation projects. An accomplished leader with a minimum of 3 -8 years of experience in software design & development. AI expert with at least 3+ years of extensive hands-on experience in building AI based applications including the latest Agentic frameworks . Working experience in leveraging RAG (Retrieval Augmented Generation), vector databases and other technologies to enhance effectiveness and relevance of the AI models. Hands-on experience in developing AI Agents based on heterogenous frameworks such as LangGraph, AutoGen, Crew AI and others. Select and fine-tune LLMs for enterprise needs, design efficient inference pipelines for system integration. Expertise in navigating through the Natural Language Understanding and developing conversational experiences. Good to Have Experience designing and developing applications and workflows using ACE framework (Autonomous Cognitive Entity) . Expertise in Python programming and developing agents/tools in an AI Agentic framework. Demonstrated experience in building data pipelines including data quality for structured and unstructured data. Ability to quickly learn and adapt to the changing technology landscape. Past expertise in .NET Core ecosystem (including ASP.NET Core, Entity Framework Core) combined with strong front-end featuring Angular/React/Javascript/Html/Css is a big plus! Hands-on experience managing full-stack web applications built upon Graph/RESTful APIs/microservice-oriented architectures hosted either natively or in containers familiarity navigating large scale data ecosystems. Skilled in efficient platform telemetry capture, ingestion, and intelligence derivation. Track record demonstrating ability to mentor peers effectively whilst maintaining exceptional attention to detail during every phase of SDLC including ideation, design, development, deployment and operational excellence. Excellent verbal/written communication abilities paired perfectly with outstanding presentation / public speaking talents.

Hands on experience in Python, Machine learning, Gen AI, Computer Vision Knowledge on Gen AI is must Required Candidate profile Model Development: Design, build, and deploy machine learning models for predictive analytics, NLP, computer vision, or recommendation systems.Data Strategy: Define and implement data strategies

Hands on experience in Python, Machine learning/Gen AI Knowledge on Gen AI is must Leadership & Strategy: Lead and mentor a team of data scientists, analysts, and engineers, ensuring best practices in data science methodologies. Required Candidate profile Model Development: Design, build, and deploy machine learning models for predictive analytics, NLP, computer vision, or recommendation systems.Data Strategy: Define and implement data strategies

Role & responsibilities As a Data Scientist specializing in Generative AI and NLP , you will be at the forefront of AI innovation. Your role will involve designing and deploying sophisticated models, including large language models (LLMs), to solve complex business problems. You will work closely with cross-functional teams to create scalable, data-driven solutions that bring AI-driven creativity and intelligence to life across various industries. Key Responsibilities : Generative AI & NLP Development : Design, develop, and deploy advanced applications and solutions using Generative AI models (e.g., GPT, LLaMA, Mistral) and NLP algorithms to solve business challenges and unlock new opportunities for our clients. Model Customization & Fine-Tuning : Apply state-of-the-art techniques like LoRA , PEFT , and fine-tuning of large language models to adapt solutions to specific use cases, ensuring high relevance and impact. Innovative Problem Solving : Leverage advanced AI methodologies to tackle real-world business problems, providing creative and scalable AI-powered solutions that drive measurable results. Data-Driven Insights : Conduct deep analysis of large datasets, uncovering insights and trends that guide decision-making, improve operational efficiencies, and fuel innovation. Cross-Functional Collaboration : Work closely with Consulting, Engineering, and other teams to integrate AI solutions into broader business strategies, ensuring the seamless deployment of AI-powered applications. Client Engagement : Collaborate with clients to understand their unique business needs, provide tailored AI solutions, and educate them on the potential of Generative AI to drive business transformation.

Job Description: 4+ Years of experience in IT Must have 3-4 yrs of experience in Data Science, Python and NLP Must have 1-2 yrs of experience in GenAI -with good hands-on experience in Text data analysis, Prompt Engineering, Cloud Vector DB ,Azure OpenAI models, developing and deploying Generative AI applications in production. Must have experience in atleast one end to end implementation of an Enterprise GenAI project. Must have 1-2 yrs of experience in API development and deployment (FastAPI, Docker containerization, Azure App service..) Must have 1-2 years of experience in designing overall Solution architecture for GenAI/AI projects. Job Location: Hydrabad/Bangalore/Pune/Chennai/Mumbai/Noida

About the Role: We are seeking a highly skilled Lead Data Scientist with 4-8 years of experience to drive innovation in machine learning, deep learning, and generative AI. The ideal candidate should have expertise in Large Language Models (LLM), Retrieval-Augmented Generation (RAG), AI Agents, and hands-on experience in LangChain or LlamaIndex, and Knowledge Graphs. The role also requires strong technical leadership and experience in AI Agent frameworks and libraries. Key Responsibilities: Lead the development and deployment of machine learning models, deep learning frameworks, and AI-driven solutions across the organization. Work closely with stakeholders to define data-driven strategies and drive innovation using AI and machine learning. Design and implement robust data pipelines and workflows in collaboration with data engineers and software developers. Develop and deploy APIs using web frameworks for seamless integration of AI/ML models into production environments. Mentor and lead a team of data scientists and engineers, providing technical guidance and fostering professional growth. Leverage LangChain or LlamaIndex to enhance model integration, document management, and data retrieval capabilities. Lead projects in Generative AI technologies, such as Large Language Models (LLM), Retrieval-Augmented Generation (RAG), and AI agents, to create innovative AI-driven products and services. Stay updated on the latest AI/ML trends, ensuring that cutting-edge methodologies are adopted across projects. Collaborate with cross-functional teams to translate business problems into technical solutions and communicate findings effectively to both technical and non-technical stakeholders. Required Skills and Qualifications: Experience: 4-8 years of experience in data science and AI/ML, with a strong foundation in machine learning, deep learning, generative AI and data engineering. Generative AI Expertise: Minimum 2 years of experience with gneretaive AI. Hands-on experience with LLMs, RAG, and AI agents. AI Agents & Frameworks: Hands-on experience with AI agent frameworks/libraries (e.g., LangGraph, CrewAI, OpenAI's Function Calling, Semantic Kernel, etc.). Programming: Strong proficiency in Python, with experience using TensorFlow, PyTorch, and Scikit-learn. LangChain & LlamaIndex: Experience integrating LLMs with structured and unstructured data. Knowledge Graphs: Expertise in building and utilizing Knowledge Graphs for AI-driven applications. SQL & NoSQL Databases: Hands-on experience with SQL (PostgreSQL, MySQL, etc.) and NoSQL (MongoDB, Cassandra, etc.) database. API Development: Experience in developing APIs using Flask or FastAPI or Django. Cloud & MLOps: Experience working with cloud providers like AWS, GCP, Azure and MLOps best practices. Excellent communication, leadership, and project management skills. Strong problem-solving ability with a focus on delivering scalable, impactful solutions. Preferred Skills: Experience with Computer Vision applications. Chain of Thought Reasoning: Familiarity with CoT prompting and reasoning techniques. Ontology: Understanding of ontologies for knowledge representation in AI systems. Data Engineering: Experience with ETL pipelines and data engineering workflows. Familiarity with big data tools like Spark, Hadoop, or distributed computing.

KEY RESPONSIBILITIES Data Science : Develop machine learning models to support recommendation systems and NLP / GEN AI projects; provide actionable insights for product and service optimization. Data Engineering : Build and maintain scalable ETL pipelines, optimize data storage solutions (data lakes, columnar formats), and ensure data accuracy for analytics. Data Analysis and Insight Generation : Skilled in analyzing complex datasets to uncover trends and patterns; generate and present insights that drive strategic decisions and enhance client services. Stakeholder Collaboration : Work with product and service teams to understand data needs and translate them into technical solutions. Skills/ Competencies Required Proficiency with Python (Pandas, NumPy), SQL, and Java. Experience with LLMs, LangChain, and Generative AI technologies. Familiarity with ML frameworks (TensorFlow, PyTorch) and data engineering tools (Spark, Kafka). Strong data analysis skills and ability to present findings to both technical and non-technical stakeholders. Proficient understanding of key data engineering concepts, such as data lakes, columnar formats, ETL tools, and BI tools. Knowledge in Machine Learning, NLP, Recommender systems, personalization, Segmentation, microservices architecture and API development. Ability to adapt to a fast-paced, dynamic work environment and learn new technologies quickly. If you find this opening suitable then please share your resume on"pooja.patil7@hdfcbank.com"

What you will be doing... As a key member of the team, you will collaborate closely with internal stakeholders to optimize processes, develop forward-thinking solutions, and enhance overall organizational success. This is an exciting opportunity to be at the forefront of innovation at Verizon and shape the future of how we work. Apply design thinking to convert abstract challenges into actionable programs that align with organizational goals. Lead and manage end-to-end implementation of innovative solutions for Legal & Security. Partner with cross-functional legal teams to understand stakeholder needs and ensure alignment across all levels. Anticipate potential issues, plan accordingly, and adapt to meet project objectives. Track and resolve bugs and issues during development and testing phases. Manage multiple Legal projects simultaneously, coordinating with cross-functional teams and leading project calls, touchpoints, and solution reviews. Document and report on all project phases, including meeting minutes, metrics, and progress updates. Keep projects on track, ensuring milestones are met and deliverables are achieved. Take on additional responsibilities as needed, demonstrating flexibility in a fast-paced and evolving environment. What Were Looking For: Were looking for someone who can maintain a strategic perspective while managing the details that ensure success. You see challenges as opportunities to problem-solve and thrive in environments with ambiguity. You excel at bringing order to complex situations and ensure every detail is addressed. If you enjoy collaborating with cross-functional teams and driving innovative solutions, this role is for you. Youll Need to Have: Bachelor's degree or four or more years of work experience. Experience in data science and analytics. Hands-on experience with SmartSheets, Google App Scripts, other BI tools, and HTML to support automation and data-driven solutions. Proven ability to present compelling business cases, performance results, and actionable recommendations. Exceptional quantitative and analytical skills, with the ability to conduct research, analyze data, and leverage tools to drive impactful results. Independent, strategic thinking with strong problem-solving abilities. Even Better If You Have: Green Belt or Black Belt certification. PMP / Agile / Design Thinking certifications or similar. Experience designing, developing, and implementing strategic plans at the organizational level. Proven ability to engage with leadership across all levels and effectively communicate business performance and strategic recommendations. Executive financial acumen, including knowledge of valuation methodologies and experience in developing financial models. In-depth knowledge of Verizon Legal and its operations. A strong understanding of legal processes and professional skills. Familiarity with contract analytics, including machine learning, NLP, and/or generative AI. Experience working with business intelligence tools and developing dashboards and reporting systems. Strong communication skills, with the ability to explain complex technical issues to both technical and non-technical stakeholders.