13 Nlp Models Jobs

As a Social Media Analyst at C5i, you will be responsible for leveraging social media listening tools to conduct timely research and reporting on consumer insights, trends, competitive analysis, product insights, and emerging consumer tensions. By combining these findings with other digital data sources, you will identify strategic recommendations and create persuasive presentations. Your role will involve understanding business objectives and measurement requirements to guide decisions, define KPI measurements, and offer insightful recommendations. You will develop a strategic social reporting and analytics cadence by identifying key areas of measurements, optimizations, and benchmarks. Furthermore, you will need to tailor your findings to provide insightful and actionable recommendations to executive-level stakeholders, utilizing efficient storytelling and visualization skills. The position requires experience in working with multiple stakeholders and projects, with the ability to prioritize projects to meet deadlines. A passion for technology is essential, including knowledge about computer hardware, builds, and gaming, or at least a willingness to learn. Additionally, you will serve as the primary point of contact for social listening support and educate audiences on best practices. You will also be expected to understand, conceptualize, and integrate AI-based analysis and automation across social media analytics. The ideal candidate for this role should have a minimum of 7+ years of experience in social media analysis and research concepts. Proficiency in social listening tools such as Talkwalker, Brandwatch, Meltwater, and Synthesio is preferred. An understanding of automation and AI implementation is crucial for this position. Proficiency in Microsoft Office Suite, particularly Excel and PowerPoint, is required. A logical mindset to read and comprehend data and reporting structures is essential, along with strong data analysis and insights writing skills. Preferred attributes for this role include the ability to write Boolean queries to extract and manipulate data, experience with visualization tools like PowerBI, Tableau, Looker, etc., knowledge of creating crawlers to capture web data, and familiarity with NLP models for sentiment analysis and thematic analysis. Join C5i to be part of a dynamic team that focuses on delivering business impact at speed and scale through AI-assisted decision-making.,

About the Role We are seeking a highly skilled Senior NLP Engineer with expertise in large language models (LLMs), prompt engineering, and transformer-based architectures. The ideal candidate will have strong experience fine-tuning, deploying, and optimizing advanced NLP models for real-world applications such as summarization, text generation, and question answering. You will collaborate with cross-functional teams to design scalable, production-ready solutions while addressing challenges such as bias, hallucinations, and knowledge cutoffs. Key Responsibilities: Fine-tune pre-trained models on domain-specific datasets to optimize for summarization, text generation, question answering, and related tasks. Prompt Engineering: Design, test, and iterate on contextually relevant prompts to guide model outputs for desired performance. Implement and refine instruction-based prompting strategies to achieve contextually accurate results. Apply zero-shot, few-shot, and many-shot learning methods to maximize model performance without extensive retraining. Leverage Chain-of-Thought (CoT) prompting for structured, step-by-step reasoning in complex tasks. Evaluate model performance using BLEU, ROUGE, and other relevant metrics; identify opportunities for improvement. Deploy trained and fine-tuned models into production environments, integrating with real-time systems and pipelines. Identify, monitor, and mitigate issues related to bias, hallucinations, and knowledge cutoffs in LLMs. Work closely with cross-functional teams (data scientists, engineers, product managers) to design scalable and efficient NLP-driven solutions. Must-Have Skills: 7+ years of overall experience in software/AI development with at least 2+ years in transformer-based NLP models. 4+ years of hands-on expertise with transformer architectures (GPT, BERT, T5, RoBERTa, etc.). Strong understanding of attention mechanisms, self-attention layers, tokenization, embeddings, and context windows. Proven experience in fine-tuning pre-trained models for NLP tasks (summarization, classification, text generation, translation, Q&A). Expertise in prompt engineering, including zero-shot, few-shot, many-shot learning, and prompt template creation. Experience with instruction-based prompting and Chain-of-Thought prompting for reasoning tasks. Proficiency in Python and NLP libraries/frameworks such as Hugging Face Transformers, SpaCy, NLTK, PyTorch, TensorFlow. Strong knowledge of model evaluation metrics (BLEU, ROUGE, perplexity, etc.). Experience in deploying models into production environments. Awareness of bias, hallucinations, and limitations in LLM outputs. Good to Have: Experience with LLM observability tools and monitoring pipelines. Exposure to cloud platforms (AWS, GCP, Azure) for scalable model deployment. Knowledge of MLOps practices for model lifecycle management. Location-Remote,Delhi NCR,Bengaluru,Chennai,Pune,Kolkata,Ahmedabad, Mumbai, Hyderabad

You will be responsible for performing a variety of moderately complex risk analytics with a focus on AI/ML models. Your role will involve resolving moderately complex issues in advanced data modeling and measuring risk. You will provide effective challenge to the models by evaluating model-related risks including input data, model assumptions and limitations, conceptual soundness, methodology, outcomes analysis, benchmarking, monitoring, and model implementation. This position requires a combination of strong quantitative skills and AI/ML technical knowledge. Your major duties will include validating Artificial Intelligence (AI), Machine Learning (ML), and Generative AI (GenAI) models independently across various categories. You will evaluate Gen AI model risk, including hallucination, prompt injection, data leakage, reproducibility, and alignment with Responsible AI principles. Additionally, you will assess model robustness, interpretability, fairness, and bias through quantitative and qualitative techniques. You will also be responsible for validating complex statistical and/or algorithmic models used across various areas within the bank. It will be crucial to ensure that model development, monitoring, and validation approaches meet regulatory expectations and internal risk management needs. Moreover, you will provide analytical or risk measurement support to help meet both internal corporate and regulatory requirements. Developing in-depth knowledge of business unit/function and complex modeling techniques used will be essential. You will need to clearly communicate the complex issues/findings of the model validation outcomes to stakeholders and keep abreast of the latest regulatory requirements around model risk management. Furthermore, you will be expected to work on varied areas of risk management as part of the centralized Model Validation team within the bank. Your knowledge and skills should include experience with Machine Learning models, strong knowledge of AI/ML techniques, experience in validating machine learning models, familiarity with GenAI risks and controls, and understanding of models used in stress testing, CCAR, CECL, BASEL regulations, among others. Excellent oral and written communication skills, knowledge of risk measurement, and strong analytical and problem-solving skills are also required. Ideally, you should have an advanced degree in a quantitative discipline or Computer Science with a focus on AI/ML, along with 3 to 6 years of relevant work experience. Programming experience in Python is required, with experience in SAS and R desired. Mastery of analytical tools and strong preference for candidates with certifications in AI/ML or CFA/FRM/CQF are important. Familiarity with cloud and big data technologies is also desired. Working at Northern Trust offers opportunities for greater achievements in a flexible and collaborative work culture. Movement within the organization is encouraged, senior leaders are accessible, and you can take pride in working for a company committed to assisting the communities it serves. Join a workplace with a greater purpose and apply today to build your career with one of the world's most admired and sustainable companies. Northern Trust is committed to providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation for any part of the employment process, please contact the HR Service Center at MyHRHelp@ntrs.com. Northern Trust values an inclusive workplace and understands that flexibility means different things to different people. Apply today and discuss your flexible working requirements to achieve greater together.,

As a Program Analyst at the World Bank based in Chennai, India, you will have the opportunity to contribute to addressing global development challenges. The World Bank Group is committed to ending extreme poverty, promoting sustainable development, and increasing shared prosperity in developing countries through innovative projects and data-driven solutions. In the Global Corporate Solutions division, you will be part of a dynamic team supporting Corporate Services within the organization. This division oversees a diverse range of services, including Travel and Visa Services, Food and Conference Services, Staff Services, Mail and Shipping Services, and more. As a Program Analyst, you will work closely with stakeholders to understand reporting needs and translate them into technical solutions. Your responsibilities will include extracting and preparing data from multiple sources, ensuring data integrity and consistency, analyzing large datasets to identify trends, and developing interactive dashboards and reports using tools such as Power BI and Tableau. You will collaborate with the team to automate workflows, apply Generative AI tools for data analysis, and stay updated on industry trends in data analytics and business intelligence. To be successful in this role, you should have a Bachelor's degree in Data Science, Computer Science, Business Analytics, Statistics, or a related field, along with a minimum of 3 years of experience in data analysis or business intelligence roles. Proficiency in Power BI, Tableau, Excel, and workflow automation tools is essential. Strong analytical, problem-solving, and communication skills are key attributes for this position. If you are a data-driven professional with a passion for problem-solving and a willingness to learn and collaborate in a fast-paced environment, we encourage you to apply for this exciting opportunity at the World Bank.,

This role is for one of the Weekday's clients. We are an innovative company at the forefront of AI-driven solutions, specializing in cutting-edge technologies to solve real-world problems. We are seeking a talented and passionate Computer Vision Engineer with expertise in both Computer Vision and Natural Language Processing (NLP) to join our dynamic team. Key Responsibilities: Develop and implement state-of-the-art computer vision algorithms for image and video processing tasks such as object detection, image segmentation, feature extraction, and recognition. Design, build, and deploy NLP models for tasks such as text recognition from images (OCR), sentiment analysis, and text classification. Collaborate with data scientists and machine learning engineers to integrate computer vision and NLP models into production systems. Work with large datasets to train and fine-tune models, ensuring high accuracy and performance. Conduct research to stay updated on the latest advancements in computer vision and NLP, and apply them to ongoing projects. Optimize model performance for real-time applications on various platforms (e.g., cloud, mobile, edge devices). Analyze and preprocess datasets including images, videos, and text for training and validation. Collaborate with cross-functional teams to ensure seamless integration of computer vision and NLP components within larger applications. Qualifications: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Proven experience (3+ years) in developing computer vision solutions and NLP models. Strong proficiency in Python and relevant libraries such as OpenCV, TensorFlow, PyTorch, Keras, and scikit-learn. Hands-on experience with deep learning frameworks (e.g., CNNs, RNNs, Transformers) for both computer vision and NLP tasks. Expertise in Natural Language Processing tasks such as tokenization, text embedding, and sequence-to-sequence models. Familiarity with Optical Character Recognition (OCR) tools and techniques. Experience working with datasets for object detection, semantic segmentation, and text recognition from visual data. Proficiency in deploying and scaling machine learning models in production environments (AWS, GCP, Azure). Strong problem-solving skills and the ability to work independently and collaboratively in a team environment. Preferred Skills: Knowledge of Reinforcement Learning (RL) and how it can be applied to vision tasks. Familiarity with multimodal machine learning, integrating vision and language models. Experience in edge computing for deploying models in real-time environments. Strong understanding of cloud-based AI/ML pipelines.,

As an AI/ML Engineer Generative AI Specialist with over 5 years of experience, you will be expected to possess the following must-have skills: You should have a strong background in AI/ML frameworks such as PyTorch, TensorFlow, and proficient in Python programming. Your experience with AWS services, specifically AWS Bedrock and Lambda functions, will be crucial. Hands-on expertise in LangChain components (agents, chains, memories, parsers, document loaders), developing and optimizing GenAI, NLP models, and CrewAI is essential for this role. You should be capable of building and deploying RAG (Retrieval-Augmented Generation) systems, chatbots, and AI applications using OpenAI APIs, Ollama, Llama, and llamaparse. Advanced prompt engineering techniques like Chain of Thought (CoT) prompting should be within your skill set. Additionally, experience with Docker, CI/CD pipelines, YML files, and GitHub repository management is required. A strong understanding of system design principles, focusing on security, scalability, and performance optimization, is a must. Good-to-have skills include experience in responsible AI practices, knowledge of event-driven architecture, and familiarity with cloud deployments and Kubernetes. Experience with large-scale AI model training and fine-tuning would be beneficial. Your key responsibilities will involve designing and implementing AI/ML solutions using cutting-edge technologies to ensure scalability, efficiency, and alignment with business objectives. You will be responsible for developing and optimizing LangChain components, CrewAI, GenAI, and NLP models customized to specific applications. Building and deploying production-ready RAG systems, chatbots, and AI-driven applications utilizing OpenAI APIs, Ollama, Llama, and llamaparse will be part of your role. Leveraging AWS Bedrock and other AWS services to deliver high-performance AI solutions is crucial. You will need to apply prompt engineering techniques like Chain of Thought (CoT) prompting to enhance AI interactions, maintain CI/CD pipelines, manage YML files, and utilize GitHub for version control. Implementing containerization using Docker and deploying AI solutions in cloud environments will also fall under your responsibilities. Ensuring that solutions adhere to best practices in system design, focusing on security, performance, and efficiency considerations is essential. You will also need to incorporate responsible AI practices and ensure compliance with ethical AI guidelines. Collaboration with cross-functional teams to translate AI insights into impactful solutions and effective communication of complex technical concepts to both technical and non-technical stakeholders will be expected from you.,

Design, implement, and optimize NLP models for tasks such as text classification, sentiment analysis, named entity recognition, and language generation. - Utilize libraries such as NLTK, SpaCy, TensorFlow, or PyTorch for model development. Preprocess and clean large datasets, ensuring data quality and integrity for NLP applications. - Develop scripts to automate data extraction, transformation, and loading (ETL) processes. Work closely with data scientists, analysts, and other stakeholders to understand project requirements and deliver effective NLP solutions. - Collaborate in an Agile environment, participating in sprint planning and code reviews. Analyze and improve the performance of existing NLP models and algorithms. - Implement best practices for model evaluation and validation. Document processes, methodologies, and model performance metrics. - Present findings and insights to technical and non-technical stakeholders.

Key Responsibilities: Hands-on Development: Develop and implement machine learning models and algorithms , including supervised, unsupervised, deep learning, and reinforcement learning techniques. Implement Generative AI solutions using technologies like RAG (Retrieval-Augmented Generation), Vector DBs , and frameworks such as LangChain and Hugging Face, Agentic AI . Utilize popular AI/ML frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn . Design and deploy NLP models and techniques , including text classification, RNNs, CNNs, and Transformer-based models like BERT. Ensure robust end-to-end AI/ML solutions, from data preprocessing and feature engineering to model deployment and monitoring. Technical Proficiency: Demonstrate strong programming skills in languages commonly used for data science and ML, particularly Python . Leverage cloud platforms and services for AI/ML, especially AWS , with knowledge of AWS Sagemaker, Lambda, DynamoDB, S3 , and other AWS resources. Mentorship: Mentor and coach a team of data scientists and machine learning engineers, fostering skill development and professional growth. Provide technical guidance and support, helping team members overcome challenges and achieve project goals. Set technical direction and strategy for AI/ML projects, ensuring alignment with business goals and objectives. Facilitate knowledge sharing and collaboration within the team, promoting best practices and continuous learning. Strategic Advisory: Collaborate with cross-functional teams to integrate AI/ML solutions into business processes and products. Provide strategic insights and recommendations to support decision-making processes. Communicate effectively with stakeholders at various levels, including technical and non-technical audiences. Required Skills: Extensive proficiency with generative AI technologies , including RAG, Vector DBs , and frameworks such as LangChain and Hugging Face, Agentic AI . Proficiency in machine learning algorithms and techniques , including supervised and unsupervised learning, deep learning, and reinforcement learning. Extensive proficiency with AI/ML frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn . Strong knowledge of natural language processing (NLP) techniques and models , including Transformer-based models like BERT. Proficient programming skills in Python . Proficiency with cloud platforms like AWS , including AWS Sagemaker, Lambda, DynamoDB, S3 , and other AWS resources. Proven ability to lead a team of data scientists or machine learning engineers on complex projects. Strong project management skills, with the ability to prioritize tasks, allocate resources, and meet deadlines. Excellent communication skills and the ability to convey complex technical concepts to diverse audiences. Strong problem-solving and analytical abilities. Proven ability to manage projects and activities. Preferred Skills: Proficiency in setting technical direction and strategy for AI/ML projects. Knowledge of the Insurance domain. Ability to mentor and coach junior team members, fostering growth and development. Proven track record of successfully managing AI/ML projects from conception to deployment.

As an LLM Expert with 3+ years of experience, you should have a strong background in designing and tuning advanced models. You must have at least 3 years of experience in LLM, NLP Models, and Machine Learning, along with 2.5 years of experience in AI. Excellent communication skills are essential for this role, as well as previous experience in team handling. Professionals with backgrounds such as Datascientist, Data Annotator AI, and AI Engineer are encouraged to apply. This position is based in Bangalore and is a full-time role with a day shift schedule. The work location is in person.,

Title: Senior Data Scientist Years of Experience : 8+ years *Location: The selected candidate is required to work onsite at our Chennai location for the initial six-month project training and execution period. After the six months , the candidate will be offered remote opportunities.* Job Description The Senior Data Scientist will lead the development and implementation of advanced analytics and AI/ML models to solve complex business problems. This role requires deep statistical expertise, hands-on model building experience, and the ability to translate raw data into strategic insights. The candidate will collaborate with business stakeholders, data engineers, and AI engineers to deploy production-grade models that drive innovation and value. Key responsibilities Lead end-to-end model lifecycle: data exploration, feature engineering, model training, validation, deployment, and monitoring Develop predictive models, recommendation systems, anomaly detection, NLP models, and generative AI applications Conduct statistical analysis and hypothesis testing for business experimentation Optimize model performance using hyperparameter tuning, ensemble methods, and explainable AI (XAI) Collaborate with data engineering teams to improve data pipelines and quality Document methodologies, build reusable ML components, and publish technical artifacts Mentor junior data scientists and contribute to CoE-wide model governance Technical Skills ML Frameworks: Scikit-learn, TensorFlow, PyTorch, XGBoost Statistical tools: Python (NumPy, Pandas, SciPy), R, SAS NLP & LLMs: Hugging Face Transformers, GPT APIs, BERT, LangChain Model deployment: MLflow, Docker, Azure ML, AWS Sagemaker Data visualization: Power BI, Tableau, Plotly, Seaborn SQL and NoSQL (CosmosDB, MongoDB) Git, CI/CD tools, and model monitoring platforms Qualification Masters in Data Science, Statistics, Mathematics, or Computer Science Microsoft Certified: Azure Data Scientist Associate or equivalent Proven success in delivering production-ready ML models with measurable business impact Publications or patents in AI/ML will be considered a strong advantage.

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

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

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