9 T5 Jobs

As an AIML - LLM Gen AI Engineer, your primary responsibility will be to design, develop, and implement solutions using transformer-based models for various Natural Language Processing (NLP) tasks. This includes tasks such as text generation, summarization, question answering, classification, and translation. You will be working extensively with transformer models like GPT, BERT, T5, RoBERTa, and similar architectures. Your deep understanding of model architectures, attention mechanisms, and self-attention layers will be crucial in effectively utilizing Large Language Models (LLMs) to generate human-like text. You will lead efforts in fine-tuning pre-trained LLMs and other transformer models on domain-specific datasets to optimize performance for specialized NLP tasks. In your role, you will apply your knowledge of attention mechanisms, context windows, tokenization, and embedding layers in model development and optimization. It will be essential to address and mitigate issues related to biases, hallucinations, and knowledge cutoffs that can impact LLM performance and output quality. You will craft clear, concise, and contextually relevant prompts to guide LLMs towards generating desired outputs, including the use of instruction-based prompting. Additionally, you will implement and experiment with zero-shot, few-shot, and many-shot learning techniques to maximize model performance without extensive retraining. Your iterative approach to prompt engineering strategies will involve refining outputs, rigorously testing model performance, and ensuring consistent and high-quality results. You will also be responsible for creating prompt templates for repetitive tasks that are adaptable to different contexts and inputs. Expertise in chain-of-thought (CoT) prompting will enable you to guide LLMs through complex reasoning tasks by encouraging step-by-step breakdowns. Your contribution will span the entire lifecycle of machine learning models in an NLP context, including training, fine-tuning, and deployment. **Required Skills & Qualifications:** - A minimum of 8 years of experience working with transformer-based models and NLP tasks, focusing on text generation, summarization, question answering, classification, and similar applications. - Proficiency in transformer models such as GPT, BERT, T5, RoBERTa, and foundational models. - Strong familiarity with model architectures, attention mechanisms, and self-attention layers for generating human-like text. - Proven experience in fine-tuning pre-trained models on domain-specific datasets for various NLP tasks. - Knowledge of attention mechanisms, context windows, tokenization, and embedding layers. - Awareness of biases, hallucinations, and knowledge cutoffs affecting LLM performance. - Ability to craft clear, concise, and contextually relevant prompts for LLMs. - Experience in zero-shot, few-shot, and many-shot learning techniques. - Proficiency in Python and NLP libraries like Hugging Face Transformers, SpaCy, NLTK. - Solid experience in training, fine-tuning, and deploying ML models in an NLP context. - Strong problem-solving skills and analytical mindset. - Excellent communication and collaboration abilities for remote or hybrid work environments. - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or related quantitative field. This role requires a combination of technical expertise in AI/ML, NLP, and transformer models, along with strong problem-solving and communication skills to achieve effective results in the field.,

You are a highly skilled AI/ML/Gen AI Data Scientist with expertise in Generative AI, Machine Learning, Deep Learning, and Natural Language Processing (NLP). You have a strong foundation in Python-based AI frameworks and experience in developing, deploying, and optimizing AI models for real-world applications. Your responsibilities include developing and implementing AI/ML models, working with Deep Learning architectures like Transformers (BERT, GPT, LLaMA) and CNNs/RNNs, fine-tuning and optimizing Large Language Models (LLMs) for various applications, designing and training custom Machine Learning models using structured and unstructured data, leveraging NLP techniques such as text summarization and Named Entity Recognition (NER), implementing ML pipelines, and deploying models in cloud environments (AWS/GCP/Azure). You will collaborate with cross-functional teams to integrate AI-driven solutions into business applications and stay updated with the latest AI advancements to apply innovative techniques to improve model performance. To qualify for this role, you should have 1 to 3 years of experience in AI/ML, Deep Learning, and Generative AI, strong proficiency in Python and ML frameworks like TensorFlow, PyTorch, Hugging Face, Scikit-learn, hands-on experience with NLP models including BERT, GPT, T5, LLaMA, and Stable Diffusion, expertise in data preprocessing, feature engineering, and model evaluation, experience with MLOps, cloud-based AI deployment, and containerization (Docker, Kubernetes), knowledge of vector databases and retrieval-augmented generation (RAG) techniques, ability to fine-tune LLMs and work with prompt engineering, strong problem-solving skills, and the ability to work in agile environments. You should hold a Bachelor's, Master's, or PhD in Computer Science, Artificial Intelligence, or Information Technology. Preferred skills include experience with Reinforcement Learning (RLHF) and multi-modal AI, familiarity with AutoML, Responsible AI (RAI), and AI Ethics, exposure to Graph Neural Networks (GNNs) and time-series forecasting, contributions to open-source AI projects or research papers. Your skills should encompass Machine Learning (ML), Generative AI, Artificial Intelligence (AI), Python, and Large Language Models (LLM).,

As an AI/ML & GenAI Developer Intern at ArgyleEnigma Tech Labs working on the FinDocGPT project, you will be part of a groundbreaking initiative to make complex financial documents easily understandable for millions of Indians. This internship opportunity offers a stipend ranging from 8,000 to 12,000 INR per month for a duration of 6 months, starting immediately. At FinDocGPT, we are dedicated to leveraging cutting-edge AI/ML and GenAI technologies to provide a transformative solution that bridges the financial literacy gap in India. Our product, FinDocGPT, is India's first AI-powered assistant that decodes intricate financial documents into simple, regional language, covering areas such as health insurance, loans, and mutual fund terms and conditions. Supported by Google for Startups and the Reserve Bank Innovation Hub, we are on a mission to empower individuals by offering financial information in a language they understand. As an AI/ML & Generative AI Developer Intern, you will have the opportunity to gain hands-on experience in deploying GenAI models, NLP pipelines, and ML-based document processing. Your responsibilities will include working on document classification, NER, and summarization using advanced LLMs such as LLaMA, Mistral, Groq, and open-source models. Additionally, you will preprocess, clean, and structure financial documents in various formats like PDFs, scans, and emails. Collaborating with the product and design teams, you will contribute to building smart and user-friendly interfaces. To excel in this role, you should possess a strong understanding of Python, NLP, and basic ML concepts. Familiarity with transformers like BERT, T5, or GPT architectures is essential. Experience, even in an academic setting, with HuggingFace, LangChain, or LLM APIs is preferred. Knowledge of Google Cloud, AWS, or Docker would be a bonus. We are looking for individuals who are eager to learn, experiment quickly, and create a tangible impact. By joining us, you will receive direct mentorship from industry experts with backgrounds in companies such as Morgan Stanley, PIMCO, and Google. You will gain real-world exposure to AI applications tailored for the Indian market and have the opportunity to transition into a full-time role based on your performance. Your work will directly contribute to enhancing financial inclusion in India. To apply for this internship, please send your CV, GitHub/portfolio, and a brief statement explaining why you are interested in this role to info@argyleenigma.com or apply via https://tinyurl.com/hr-aetl with the subject line "Internship Application - FinDocGPT." This internship is based in Gandhinagar, Gujarat, and requires in-person work. The expected start date is 01/08/2025.,

Role & responsibilities Design, prototype, and deploy AI-driven applications leveraging LLMs (GPT-4, Perplexity, Claude, Gemini, etc.) and open-source transformer models. Lead or co-lead end-to-end AI/GenAI solutions : from data ingestion, entity extraction, and semantic search to user-facing interfaces. Implement RAG (Retrieval-Augmented Generation) architectures, knowledge grounding pipelines, and prompt orchestration logic. Fine-tune transformer models (BERT, RoBERTa, T5, LLaMA) on custom datasets for use cases like: Document understanding Conversational AI Question answering Summarization & Topic Modeling Integrate LLM workflows into scalable backend architectures with APIs and frontends. Work closely with business teams and pharma SMEs to translate requirements into GenAI solutions . Mentor junior engineers and contribute to AI capability development across the organization. Tech Stack & Skills Required Programming & Libraries : Python, FastAPI, LangChain, Pandas, PyTorch/TensorFlow, Transformers (HuggingFace), OpenAI SDK. Data Extraction & Processing : PDFMiner, PyMuPDF, Tabula, PyPDF2, Tesseract OCR, python-pptx. Gen AI / LLMs : OpenAI (GPT), Gemini, Perplexity, Cohere, DeepSeek, Mistral, LLaMA, BERT, RoBERTa, T5, Falcon. Use Cases : NER, Summarization, QA, Document Parsing, Clustering, Topic Modeling, QA over docs. Embedding & Vector Databases : Pinecone, FAISS, ChromaDB. RAG & Retrieval Pipelines : LangChain, Haystack, custom retrievers. Frontend/Backend Integration : React (preferred), FastAPI/Flask, REST/GraphQL APIs. Versioning & Deployment : Git, Docker, CI/CD (basic), cloud knowledge is a plus (AWS/GCP/Azure). Preferred candidate profile Degree in Computer Science, Engineering, Data Science, or related field (BE/BTech/MTech/MCA). 35 years of hands-on experience in AI/ML/NLP/LLM solution development. Strong understanding of GenAI, Prompt Engineering, LLM internals , and multi-layered data architectures. Exposure to pharma/healthcare domain is a significant plus. Excellent problem-solving skills, self-learner, and ability to work in cross-functonal teams. Experience developing new applications within an agile environment preferred. Ability to work independently and as part of a team. Exposure to MLOPs will be an added advantage.

As a NLP & Generative AI Engineer at Gigaforce, you will be part of our dynamic AI/ML team based in Noida, working on cutting-edge technologies to revolutionize the insurance claims processing industry. We are a California-based InsurTech company with a strong focus on innovation and digital transformation in the Property and Casualty sector. You must have a minimum of 2 years of hands-on experience in traditional machine learning, natural language processing, and modern generative AI techniques to be considered for this role. We are looking for individuals who are passionate about deploying GenAI solutions to production, working with open-source technologies, and handling document-centric pipelines efficiently. Your main responsibilities will include building and deploying NLP and GenAI-driven products focusing on document understanding, summarization, classification, and retrieval. You will be designing and implementing models using LLMs such as GPT, T5, and BERT, along with working on scalable, cloud-based pipelines for training, serving, and monitoring models. Collaboration is key at Gigaforce, and you will work closely with cross-functional teams including data scientists, ML engineers, product managers, and developers. Additionally, you will contribute to open-source tools and frameworks in the ML ecosystem, deploying production-ready solutions using MLOps practices, and working on distributed/cloud systems with GPU-accelerated workflows. To be successful in this role, you should have a strong grasp of traditional ML algorithms, NLP fundamentals, and modern NLP & GenAI models. Proficiency in Python, experience with cloud platforms like AWS SageMaker, GCP, or Azure ML, and familiarity with MLOps tools and distributed computing are essential. Experience with document processing pipelines and understanding insurance-related documents is a plus. If you are looking for a challenging role where you can lead the design, development, and deployment of innovative AI/ML solutions in the insurance industry, then this position at Gigaforce is the perfect opportunity for you. Join us in our mission to transform the claims lifecycle into an intelligent, end-to-end digital experience.,

At EY, youll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And were counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY-Consulting AI Enabled Automation Developer Staff -Python We are looking to hire people with strong AI Enabled Automation skills and who are interested in learning new technologies in the process automation space Azure . GenAI , large Lang Models(LLM). RAG ,Vector DB , Graph DB ,Python At EY, youll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And were counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Responsibilities Development and implementation of AI enabled automation solutions, ensuring alignment with business objectives. Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals, demonstrating the potential of AI enabled automation applications. Ensure seamless integration of optimized solutions into the overall product or system Collaborate with cross-functional teams to understand requirements, to integrate solutions into cloud environments (Azure, GCP, AWS, etc.) and ensure it aligns with business goals and user needs Educate team on best practices and keep updated on the latest tech advancements to bring innovative solutions to the project Requirements 2 to 3 years of relevant professional experience Expertise in Python programming including experience with Al/machine learning frameworks like TensorFlow, PyTorch, Keras, Langchain, MLflow, Promtflow(Good to have) 1-2 years of working knowledge of NLP and LLMs like BERT, GPT-3/4, T5, etc. Knowledge of how these models work and how to fine-tune them Expertise in prompt engineering principles and techniques like chain of thought, in-context learning, tree of thought, etc. Knowledge of retrieval augmented generation (RAG) Knowledge of Knowledge Graph RAG Strong analytical and problem-solving skills with the ability to think critically and troubleshoot issues Excellent communication skills, both verbal and written in English What we look for A Team of people with commercial acumen, technical experience and enthusiasm to learn new things in this fast-moving environment An opportunity to be a part of market-leading, multi-disciplinary team of 1400 + professionals, in the only integrated global transaction business worldwide. Opportunities to work with EY Advisory practices globally with leading businesses across a range of industries What working at EY offers At EY, were dedicated to helping our clients, from startups to Fortune 500 companies and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way thats right for you EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.,

Research & Development - AI Prompt Engineer Company Overview : We are Motive - the worlds leading provider of device management for mobile, fixed and IOT as well as managing the omni-channel customer experience which through its business logic drives actions, runs proactive care campaigns and improves customer satisfaction. Deployed by leading service providers worldwide, Motives device management and service management platform drive revenue, reduce customer care costs and automate each customer interaction. A relaunched brand with a long history and pedigree, at Motive we differentiate ourselves by creating innovative technical solutions, packaging them in ways that simplify operational complexity and time to market, and we never forget that we only succeed when our customers succeed. As a member of the Motive team, you will share a passion for being part of an exciting team of talented individuals, with a focus on building sustained long-term growth, and a fantastic place to work. Surrounded by individuals of exceptional ability and commitment, you will have the opportunity both to contribute to our continued business success, and to also invest in your own personal development. At Motive we hire only passionate team orientated people to join our business. Are you one of them? Position Summary: As a Research and Development AI Prompt Engineer, you will be at the forefront of creating and enhancing our software products. You will maximize the value of the R&D team’s delivery in research, design, prototyping, and development of new features and solutions. In this role, you will focus on developing, optimizing, and fine-tuning AI prompts for various natural language processing (NLP) and generative AI systems. You will work closely with software engineers to improve model outputs, refine AI understanding, and ensure the quality and accuracy of generated content. As an AI Prompt Engineer, you’ll play a key role in creating effective and efficient prompts that maximize the performance of AI models, particularly those focused on tasks such as anomaly detection, prediction, question answering, summarization, and more. Main Responsibility Areas: Prompt Design and Optimization Develop, test, and optimize natural language prompts for a variety of tasks, ensuring that AI models produce accurate, contextually relevant, and high-quality responses Experiment with different prompt engineering techniques, strategies, and styles to improve AI model outputs in various scenarios (e.g., anomaly detection, chatbot interactions, code generation, etc.) Analyze and refine existing prompts to ensure the desired AI model behavior AI Model Fine-tuning Collaborate with R&D and Professional Services software engineers to fine-tune pre-trained models using custom prompts for specific business requirements or user needs. Conduct prompt-based testing and validation to assess model performance and quality. Develop feedback loops to iteratively improve prompt designs based on model output quality. Performance Optimization: Analyze AI model outputs and fine tune prompts to improve accuracy and performance. Work closely with R&D software engineers to integrate prompt-engineered models into production systems and applications. Partner with product managers and UX/UI designers to understand user needs and ensure that AI-generated content aligns with user expectations and business goals. Document prompt engineering strategies, guidelines, and best practices. Maintain detailed records of model performance metrics and improvements over time. Provide regular updates to stakeholders on prompt optimization results and model performance. Stay up-to-date with the latest trends and techniques in AI, NLP, and prompt engineering. Create prototypes and proof-of-concept models to demonstrate the feasibility and potential of new ideas. Key Skills & Competencies: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Linguistics, AI, Data Science, or a related field. Advanced degrees and relevant certifications are a plus. Strong understanding of natural language processing (NLP) techniques and machine learning models (e.g., GPT, BERT, T5). Experience with AI prompt engineering, fine-tuning, and content generation tasks. Familiarity with large-scale pre-trained models, including transformers and generative models. Proficiency in programming languages such as Python, with a focus on libraries like Hugging Face, TensorFlow, PyTorch, or OpenAI’s API. Troubleshooting skills. Familiarity with AI platforms and cloud computing services (e.g., AWS, GCP, Azure). Expertise in Atlassian Jira and Confluence tools as well as Microsoft SharePoint Excellent verbal and written communication skills. Ability to articulate technical concepts to both technical and non-technical stakeholders. Ability to work effectively in a collaborative team environment. Strong interpersonal skills and a proactive attitude. Ability to quickly learn and apply new technologies. Flexibility to adapt to changing priorities and project requirements. Work Experience Requirements: Experience working with generative models such as GPT-3/4, BERT, or T5. Familiarity with conversational AI, chatbots, and interactive AI systems. Experience with data labeling, model evaluation, and data annotation. A strong portfolio showcasing previous work in prompt design or AI-driven NLP systems. Knowledge of AI ethics, bias mitigation, and content moderation techniques. Limitations and Disclaimer The above job description is meant to describe the general nature and level of work being performed; it should not be construed as an exhaustive list of all responsibilities, duties and skills required for the position. All job requirements are subject to possible modification to reasonably accommodate individuals with disabilities. Some requirements may exclude individuals who pose a direct threat or significant risk to the health and safety of themselves or other employees. This job description in no way states or implies that these are the only duties to be performed by the employee occupying this position. Employees will be required to follow any other job-related instructions and to perform other job-related duties requested by their manager.

Roles and Responsibilities: Model Expertise : Work with transformer models such as GPT , BERT , T5 , RoBERTa , and others for a variety of NLP tasks, including text generation, summarization, classification, and translation. Model Fine-Tuning : Fine-tune pre-trained models on domain-specific datasets to improve performance for specific applications such as summarization, text generation, and question answering. Prompt Engineering : Craft clear, concise, and contextually relevant prompts to guide transformer-based models towards generating desired outputs for specific tasks. Iterate on prompts to optimize model performance. Instruction-Based Prompting : Implement instruction-based prompting to guide the model toward achieving specific goals, ensuring that the outputs are contextually accurate and aligned with task objectives. Zero-shot, Few-shot, Many-shot Learning : Utilize zero-shot , few-shot , and many-shot learning techniques to improve model performance without the need for full retraining. Chain-of-Thought (CoT) Prompting : Implement Chain-of-Thought (CoT) prompting to guide models through complex reasoning tasks, ensuring that the outputs are logically structured and provide step-by-step explanations. Model Evaluation : Use evaluation metrics such as BLEU , ROUGE , and other relevant metrics to assess and improve the performance of models for various NLP tasks. Model Deployment : Support the deployment of trained models into production environments and integrate them into existing systems for real-time applications. Bias Awareness : Be aware of and mitigate issues related to bias , hallucinations , and knowledge cutoffs in LLMs, ensuring high-quality and reliable outputs. Collaboration : Collaborate with cross-functional teams including engineers, data scientists, and product managers to deliver efficient and scalable NLP solutions. Must Have Skill Overall 7 years with at least 5+ years of experience working with transformer-based models and NLP tasks , with a focus on text generation , summarization , question answering , classification , and similar tasks. Expertise in transformer models like GPT (Generative Pre-trained Transformer) , BERT (Bidirectional Encoder Representations from Transformers) , T5 (Text-to-Text Transfer Transformer) , RoBERTa , and similar models. Familiarity with model architectures, attention mechanisms, and self-attention layers that enable LLMs to generate human-like text. Experience in fine-tuning pre-trained models on domain-specific datasets for tasks such as text generation , summarization , question answering , classification , and translation . Familiarity with concepts like attention mechanisms , context windows , tokenization , and embedding layers . Awareness of biases , hallucinations , and knowledge cutoffs that can affect LLM performance and output quality. Expertise in crafting clear, concise, and contextually relevant prompts to guide LLMs towards generating desired outputs. Experience in instruction-based prompting Use of zero-shot , few-shot , and many-shot learning techniques for maximizing model performance without retraining. Experience in iterating on prompts to refine outputs, test model performance, and ensure consistent results. Crafting prompt templates for repetitive tasks, ensuring prompts are adaptable to different contexts and inputs. Expertise in chain-of-thought (CoT) prompting to guide LLMs through complex reasoning tasks by encouraging step-by-step breakdowns. Proficiency in Python and experience with NLP libraries (e.g., Hugging Face, SpaCy, NLTK). Experience with transformer-based models (e.g., GPT, BERT, T5) for text generation tasks. Experience in training, fine-tuning, and deploying machine learning models in an NLP context. Understanding of model evaluation metrics (e.g., BLEU, ROUGE) Qualification: BE/B.Tech or Equivalent degree in Computer Science or related field. Excellent communication skills in English, both verbal and written

We are looking for Indias top 1% NLP Engineers for a unique job opportunity to work with the industry leaders Who can be a part of the community? We are looking for top-tier Natural Language Processing Engineers with experience in text analytics, LLMs, and speech processing If you have experience in this field then this is your chance to collaborate with industry leaders Whats in it for you? Pay above market standards The role is going to be contract based with project timelines from 2 12 months, or freelancing Be a part of Elite Community of professionals who can solve complex AI challenges Work location could be: Remote (Highly likely) Onsite on client location Deccan AIs Office: Hyderabad or Bangalore Responsibilities: Develop and optimize NLP models (NER, summarization, sentiment analysis) using transformer architectures (BERT, GPT, T5, LLaMA) Build scalable NLP pipelines for real-time and batch processing of large text data and optimize models for performance and deploy on cloud platforms (AWS, GCP, Azure) Implement CI/CD pipelines for automated training, deployment, and monitoring & integrate NLP models with search engines, recommendation systems, and RAG techniques Ensure ethical AI practices and mentor junior engineers Required Skills: Expert Python skills with NLP libraries (Hugging Face, SpaCy, NLTK) Experience with transformer-based models (BERT, GPT, T5) and deploying at scale (Flask, Kubernetes, cloud services) Strong knowledge of model optimization, data pipelines (Spark, Dask), and vector databases Familiar with MLOps, CI/CD (MLflow, DVC), cloud platforms, and data privacy regulations Nice to Have: Experience with multimodal AI, conversational AI (Rasa, OpenAI API), graph-based NLP, knowledge graphs, and A/B testing for model improvement Contributions to open-source NLP projects or a strong publication record What are the next steps? Register on our Soul AI website Our team will review your profile Clear all the screening rounds: Clear the assessments once you are shortlisted Profile matching and Project Allocation: Be patient while we align your skills and preferences with the available project Skip the Noise Focus on Opportunities Built for You! Location : - Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune,India