299 Hugging Face Jobs - Page 11

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose - the relentless pursuit of a world that works better for people - we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. Inviting applications for the role of Principal Consultant - Generative AI In this role, you will be responsible for creating cutting-edge artificial intelligence solutions that possess a broad understanding of diverse tasks and domains. You will contribute to the development of intelligent systems capable of adapting and learning across a wide range of applications. Responsibilities . experience in Cloud & Generative AI . Hands-on knowledge in Large Language Models from OpenAI, Meta, Google, Hugging Face etc. - demonstrate ability to implement solutions leveraging LLMs . Working knowledge of generative models, prompt engineering, fine-tuning - to implement innovative AI use cases . Collaborate with the architect to develop prototypes, conduct PoCs . Collaborate with service line teams to design, implement and manage Gen-AI solutions . Define and document best practices and strategies regarding deployment and infrastructure maintenance . Good understanding of AWS/Azure primarily focus on AI ecosystems such as Elasticsearch, Azure OpenAI/Cognitive services . Ability to write robust code in Python Java, React, RDBMS (Postgres) - Transactional and Analytical databases . (More than 1 language including Python is preferred) . Experience with Docker and Kubernetes . Experience with Agile Development. Qualifications we seek in you! Minimum Qualifications / Skills . BE/B.TECH . Strong understanding of generative AI models and algorithms. . Proficiency in at least one Generative AI Model (OpenAI ChatGPT, llama, Claude 2, etc.). Preferred Qualifications/ Skills . Self-starter . Highly motivated/passionate for new technologies, engineering mindset . Strong teamwork, problem-solving, and analytical skills . Good communication Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Get to know us at www.genpact.com and on X, Facebook, LinkedIn, and YouTube. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Role : Data Scientist Experience: 610 Years Salary : 35 L Upto Location : Bangalore Notice Period: 30 Days max ( Immediate Joiners Preferred ) Note : We are Open for both Contract or FTE Job Description: We are seeking a Data Scientist with strong experience in natural language processing and generative AI to build intelligent systems that extract information from PDFs, power chatbots, and implement retrieval-augmented generation (RAG) solutions. The ideal candidate should have a solid foundation in machine learning, experience working with unstructured text data. Key Responsibilities: Design and implement pipelines for extracting structured data from PDF documents using tools like PyMuPDF, PDFPlumber, or OCR libraries. Develop and fine-tune RAG pipelines combining vector databases (e.g., FAISS, Chroma) with LLMs for document-based question answering. Build and optimize conversational agents (chatbots) that use domain-specific data and generative AI models. Train and evaluate machine learning and NLP models for classification, entity extraction, summarization, etc. Collaborate with engineering and product teams to integrate AI capabilities into production systems. Monitor model performance and continually improve accuracy and relevance of generated responses. Requirements: Strong Python skills and experience with libraries like Hugging Face Transformers, LangChain, or LlamaIndex. Strong knowledge of ABC cloud tools (AWS or Azure) Familiarity with vector databases and embedding models (OpenAI, Cohere, SentenceTransformers). Experience with PDF data extraction techniques and tools. Solid understanding of supervised/unsupervised ML, deep learning, and NLP techniques. Experience working with LLMs and knowledge of prompt engineering and fine-tuning. Bachelors or Masters degree in Computer Science, Data Science, or a related field.

Role Responsibilities: Build and deploy LLM-based NLP and content generation solutions Fine-tune models, develop RAG pipelines, and conduct prompt engineering Integrate AI workflows using Python, LangChain, and vector databases Optimize AI systems for production performance and cost Key Deliverables: Scalable GenAI solutions integrated into enterprise apps Custom LLMs with fine-tuning and embeddings Deployment-ready ML pipelines using AWS/Azure/GCP Documentation and collaboration on ethical AI practices

Role Responsibilities: Build and deploy LLM-based NLP and content generation solutions Fine-tune models, develop RAG pipelines, and conduct prompt engineering Integrate AI workflows using Python, LangChain, and vector databases Optimize AI systems for production performance and cost Key Deliverables: Scalable GenAI solutions integrated into enterprise apps Custom LLMs with fine-tuning and embeddings Deployment-ready ML pipelines using AWS/Azure/GCP Documentation and collaboration on ethical AI practices

Job Summary: We are looking for a highly capable and automation-driven MLOps Engineer with 2+ years of experience in building and managing end-to-end ML infrastructure. This role focuses on operationalizing ML pipelines using tools like DVC, MLflow, Kubeflow, and Airflow, while ensuring efficient deployment, versioning, and monitoring of machine learning and Generative AI models across GPU-based cloud infrastructure (AWS/GCP). The ideal candidate will also have experience in multi-modal orchestration, model drift detection, and CI/CD for ML systems. Key Responsibilities: Develop, automate, and maintain scalable ML pipelines using tools such as Kubeflow, MLflow, Airflow, and DVC. Set up and manage CI/CD pipelines tailored to ML workflows, ensuring reliable model training, testing, and deployment. Containerize ML services using Docker and orchestrate them using Kubernetes in both development and production environments. Manage GPU infrastructure and cloud-based deployments (AWS, GCP) for high-performance training and inference. Integrate Hugging Face models and multi-modal AI systems into robust deployment frameworks. Monitor deployed models for drift, performance degradation, and inference bottlenecks, enabling continuous feedback and retraining. Ensure proper model versioning, lineage, and reproducibility for audit and compliance. Collaborate with data scientists, ML engineers, and DevOps teams to build reliable and efficient MLOps systems. Support Generative AI model deployment with scalable architecture and automation-first practices. Qualifications: 2+ years of experience in MLOps, DevOps for ML, or Machine Learning Engineering. Hands-on experience with MLflow, DVC, Kubeflow, Airflow, and CI/CD tools for ML. Proficiency in containerization and orchestration using Docker and Kubernetes. Experience with GPU infrastructure, including setup, scaling, and cost optimization on AWS or GCP. Familiarity with model monitoring, drift detection, and production-grade deployment pipelines. Good understanding of model lifecycle management, reproducibility, and compliance. Preferred Qualifications : Experience deploying Generative AI or multi-modal models in production. Knowledge of Hugging Face Transformers, model quantization, and resource-efficient inference. Familiarity with MLOps frameworks and observability stacks. Experience with security, governance, and compliance in ML environments. Location-Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

- Data Scientist -6+ years of experience in data science, with at least 2 years focused on LLMs or Generative AI. -Proven implementation experience in Data Science, Machine Learning, Deep Learning, and NLP for multiple domains. -Strong programming skills in Python, with experience in libraries such as Transformers (Hugging Face), PyTorch, or TensorFlow. -Hands-on experience with fine-tuning, prompt engineering, RAG (Retrieval-Augmented Generation), and LLM evaluation. -Familiarity with vector databases and embedding techniques. -Experience deploying models using APIs, Docker, and cloud platforms -Strong analytical, problem-solving, and communication skills. -Experience in ML Ops, Model deployment, Model lifecycle and management

ONLY 30 DAYS JOINERS Hello I hope you're doing well. We are currently hiring for an exciting opportunity with one of our top clients in the field of Generative AI . Based on your background, I believe this role could be a strong match for your expertise. Role Highlights: Location: Bangalore/Chennai/Kolkata/Pune/Hyderabad Experience Required: 11 -16 Years Notice Period: Maximum 30 Days CTC: As per market standards Mandatory Skills: Gen AI, LLM, ML/DL/NLP, RAG, LangChain, Mistral, Llama, Hugging Face, Python, TensorFlow, PyTorch, Django, Vector DB Preferred Skills: GCP/Azure/AWS, Databricks, MLOps (Kubeflow/Mlflow), Kubernetes, GitHub/Bitbucket, ADO, GPT-4 Key Responsibilities: Develop and implement advanced Generative AI models. Apply ML/DL algorithms for real-world applications across NLP and vision domains. Collaborate on data preprocessing, model training, and deployment. Drive innovation by staying current with industry trends and R&D in Gen AI. Ensure responsible AI practices and performance monitoring post-deployment. Mentor junior members and lead AI-driven project initiatives. If you're interested or know someone who fits this role, please share your updated resume and current CTC/Notice Period details. WhatsApp: 987153039 Email: shweta.gupta@sspearhead.com Warm Regards SHWETA GUPTA || Senior Recruitment Specialist Spearhead Professional Services Call/ WhatsApp: 9871530393 LinkedIn Profile: shwetagupta1810

We are seeking a highly experienced and technically adept Lead AI/ML Engineer to spearhead the development and deployment of cutting-edge AI solutions, with a focus on Generative AI and Natural Language Processing (NLP). The ideal candidate will be responsible for leading a high-performing team, architecting scalable ML systems, and driving innovation across AI/ML projects using modern toolchains and cloud-native technologies. Key Responsibilities Team Leadership: Lead, mentor, and manage a team of data scientists and ML engineers; drive technical excellence and foster a culture of innovation. AI/ML Solution Development: Design and deploy end-to-end machine learning and AI solutions, including Generative AI and NLP applications. Conversational AI: Build LLM-based chatbots and document intelligence tools using frameworks like LangChain , Azure OpenAI , and Hugging Face . MLOps Execution: Implement and manage the full ML lifecycle using tools such as MLFlow , DVC , and Kubeflow to ensure reproducibility, scalability, and efficient CI/CD of ML models. Cross-functional Collaboration: Partner with business and engineering stakeholders to translate requirements into impactful AI solutions. Visualization & Insights: Develop interactive dashboards and data visualizations using Streamlit , Tableau , or Power BI for presenting model results and insights. Project Management: Own delivery of projects with clear milestones, timelines, and communication of progress and risks to stakeholders. Required Skills & Qualifications Languages & Frameworks: Proficient in Python and frameworks like TensorFlow , PyTorch , Keras , FastAPI , Django NLP & Generative AI: Hands-on experience with BERT , LLaMA , Spacy , LangChain , Hugging Face , and other LLM-based technologies MLOps Tools: Experience with MLFlow , Kubeflow , DVC , ClearML for managing ML pipelines and experiment tracking Visualization: Strong in building visualizations and apps using Power BI , Tableau , Streamlit Cloud & DevOps: Expertise with Azure ML , Azure OpenAI , Docker , Jenkins , GitHub Actions Databases & Data Engineering: Proficient with SQL/NoSQL databases and handling large-scale datasets efficiently Preferred Qualifications Masters or PhD in Computer Science, AI/ML, Data Science, or related field Experience working in agile product development environments Strong communication and presentation skills with technical and non-technical stakeholders

Responsibilities AI-Powered Software Development & API Integration Develop AI-driven applications, microservices, and automation workflows using FastAPI, Flask, or Django, ensuring cloud-native deployment and performance optimization. Integrate OpenAI APIs (GPT models, Embeddings, Function Calling) and Retrieval-Augmented Generation (RAG) techniques to enhance AI-powered document retrieval, classification, and decision-making. Data Engineering & AI Model Performance Optimization Design, build, and optimize scalable data pipelines for AI/ML workflows using Pandas, PySpark, and Dask, integrating data sources such as Kafka, AWS S3, Azure Data Lake, and Snowflake. Enhance AI model inference efficiency by implementing vector retrieval using FAISS, Pinecone, or ChromaDB, and optimize API latency with tuning techniques (temperature, top-k sampling, max tokens settings). Microservices, APIs & Security Develop scalable RESTful APIs for AI models and data services, ensuring integration with internal and external systems while securing API endpoints using OAuth, JWT, and API Key Authentication. Implement AI-powered logging, observability, and monitoring to track data pipelines, model drift, and inference accuracy, ensuring compliance with AI governance and security best practices. AI & Data Engineering Collaboration Work with AI/ML, Data Engineering, and DevOps teams to optimize AI model deployments, data pipelines, and real-time/batch processing for AI-driven solutions. Engage in Agile ceremonies, backlog refinement, and collaborative problem-solving to scale AI-powered workflows in areas like fraud detection, claims processing, and intelligent automation. Cross-Functional Coordination and Communication Collaborate with Product, UX, and Compliance teams to align AI-powered features with user needs, security policies, and regulatory frameworks (HIPAA, GDPR, SOC2). Ensure seamless integration of structured and unstructured data sources (SQL, NoSQL, vector databases) to improve AI model accuracy and retrieval efficiency. Mentorship & Knowledge Sharing Mentor junior engineers on AI model integration, API development, and scalable data engineering best practices, and conduct knowledge-sharing sessions. Education & Experience Required 12-18 years of experience in software engineering or AI/ML development, preferably in AI-driven solutions. Hands-on experience with Agile development, SDLC, CI/CD pipelines, and AI model deployment lifecycles. Bachelor's Degree or equivalent in Computer Science, Engineering, Data Science, or a related field. Proficiency in full-stack development with expertise in Python (preferred for AI), Java Experience with structured & unstructured data: SQL (PostgreSQL, MySQL, SQL Server) NoSQL (OpenSearch, Redis, Elasticsearch) Vector Databases (FAISS, Pinecone, ChromaDB) Cloud & AI Infrastructure: AWS: Lambda, SageMaker, ECS, S3 Azure: Azure OpenAI, ML Studio GenAI Frameworks & Tools: OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex, AutoGPT, CrewAI. Experience in LLM deployment, retrieval-augmented generation (RAG), and AI search optimization. Proficiency in AI model evaluation (BLEU, ROUGE, BERT Score, cosine similarity) and responsible AI deployment. Strong problem-solving skills, AI ethics awareness, and the ability to collaborate across AI, DevOps, and data engineering teams. Curiosity and eagerness to explore new AI models, tools, and best practices for scalable GenAI adoption.

Job Summary: We are seeking a passionate and skilled AI Engineer to design, develop, and deploy cutting-edge AI solutions across domains such as large language models (LLMs), computer vision, and autonomous agent workflows. You will collaborate with data scientists, researchers, and engineering teams to build intelligent systems that solve real-world problems using deep learning, transformer-based architectures, and multi-modal AI models. Key Responsibilities: Design and implement AI/ML models, especially transformer-based LLMs (e.g., BERT, GPT, LLaMA) and vision models (e.g., ViT, YOLO, Detectron2). Develop and deploy computer vision pipelines for object detection, segmentation, OCR, and image classification tasks. Build and orchestrate intelligent agent workflows using prompt engineering, memory systems, retrieval-augmented generation (RAG), and multi-agent coordination. Fine-tune and optimize pre-trained models on domain-specific datasets using frameworks like PyTorch or TensorFlow. Collaborate with cross-functional teams to understand problem requirements and translate them into scalable AI solutions. Implement inference pipelines and APIs to serve AI models efficiently using tools such as FastAPI, ONNX, or Triton Inference Server. Conduct model evaluation, benchmarking, A/B testing, and performance tuning. Stay updated with state-of-the-art research in deep learning, generative AI, and multi-modal learning. Ensure reproducibility, versioning, and documentation of all experiments and production models. Qualifications: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 35 years of hands-on experience in designing and deploying deep learning models. Strong knowledge of LLMs (e.g., GPT, BERT, T5), Vision Models (e.g., CNNs, Vision Transformers), and Computer Vision techniques. Experience building intelligent agents or using frameworks like LangChain, Haystack, AutoGPT, or similar. Proficiency in Python, with expertise in libraries such as PyTorch, TensorFlow, Hugging Face Transformers, OpenCV, and Scikit-learn. Familiarity with MLOps concepts and deployment tools (Docker, Kubernetes, MLflow). Strong understanding of NLP, image processing, model fine-tuning, and optimization. Experience with cloud platforms (AWS, GCP, Azure) and GPU environments. Excellent problem-solving, communication, and teamwork skills. Preferred Qualifications: Experience in building multi-modal AI systems (e.g., combining vision + language models). Exposure to real-time inference systems and low-latency model deployment. Contributions to open-source AI projects or research publications. Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and RAG pipelines. Locations : Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, India

Job Summary: We are seeking a highly skilled and hands-on AI Engineer with 3+ years of proven experience in building and deploying solutions using Generative AI and Large Language Models (LLMs). You will work on cutting-edge applications leveraging transformer-based architectures, fine-tuning, prompt engineering, and scalable AI deployments. This role is ideal for engineers passionate about AI research and real-world productization of generative AI technologies. Key Responsibilities: Design, develop, and deploy solutions using LLMs (e.g., GPT, LLaMA, Mistral, Claude, PaLM, etc.) for various NLP and content generation tasks. Work on fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) pipelines. Integrate LLMs into enterprise applications with APIs and orchestrate workflows using Python, LangChain, or similar frameworks. Optimize model performance, latency, and cost for production use. Collaborate with data scientists, MLOps engineers, and product managers to deliver scalable AI features. Conduct experiments, analyze results, and publish internal findings or contribute to whitepapers. Ensure ethical, secure, and responsible use of AI technologies in all implementations. Required Skills & Experience: 3+ years of hands-on experience working with Generative AI, LLMs, and NLP technologies. Strong programming skills in Python and experience with libraries like Transformers (Hugging Face), LangChain, PyTorch, TensorFlow, etc. Proven track record of fine-tuning LLMs, developing embeddings, and working with vector databases (e.g., FAISS, Pinecone, Weaviate). Experience deploying models on cloud platforms (AWS, Azure, GCP) and using ML pipelines or MLOps tools. Solid understanding of deep learning, NLP architectures, tokenization, and evaluation metrics for generative models. Experience in API development and integration of LLMs into user-facing applications. Preferred Qualifications: Masters or PhD in Computer Science, AI/ML, Data Science, or related field. Experience with OpenAI APIs, Anthropic, Cohere, or open-source LLMs (e.g., Mistral, Falcon, LLaMA 3). Understanding of RLHF (Reinforcement Learning from Human Feedback) and model alignment techniques. Contributions to open-source AI projects or publications in GenAI/LLM.

ABOUT THE ROLE Role Description: We are seeking an accomplished and visionary Data Scientist/ GenAI developer to join Amgens Enterprise Data Management team. As part of MDM team, you will be responsible for design ing , develop ing , and deploy ing Generative AI and ML models to power data-driven decisions across business domains. This role is ideal for an AI practitioner who thrives in a collaborative environment and brings a strategic mindset to applying advanced AI techniques to solve real-world problems. To succeed in this role, the candidate must have strong AI/ML, Data Science , GenAI experience along with MDM knowledge, hence the candidates having only MDM experience are not eligible for this role. Candidate must have AI/ML, data science and GenAI experience on technologies like ( PySpark / PyTorch , TensorFlow, LLM , Autogen , Hugging FaceVectorDB , Embeddings, RAGs etc ), along with knowledge of MDM (Master Data Management) Roles & Responsibilities: Develop enterprise-level GenAI applications using LLM frameworks such as Langchain, Autogen, and Hugging Face. Design and develop intelligent pipelines using PySpark, TensorFlow, and PyTorch within Databricks and AWS environments. Implement embedding models andmanage VectorStores for retrieval-augmented generation (RAG) solutions. Integrate and leverage MDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems. Utilize SQL and Python for data engineering, data wrangling, and pipeline automation. Build scalable APIs and services to serve GenAI models in production. Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems. Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations. Basic Qualifications and Experience: Masters degree with 4 - 6 years of experience in Business, Engineering, IT or related field OR Bachelors degree with 6 - 9 years of experience in Business, Engineering, IT or related field OR Diploma with 10 - 12 years of experience in Business, Engineering, IT or related field Functional Skills: Must-Have Skills: 6+ years of experience working in AI/ML or Data Science roles, including designing and implementing GenAI solutions. Extensive hands-on experience with LLM frameworks and tools such as Langchain, Autogen, Hugging Face, OpenAI APIs, and embedding models. Strong programming background with Python, PySpark, and experience in building scalable solutions using TensorFlow, PyTorch, and SK-Learn. Proven track record of building and deploying AI/ML applications in cloud environments such as AWS. Expertise in developing APIs, automation pipelines, and serving GenAI models using frameworks like Django, FastAPI, and DataBricks. Solid experience integrating and managing MDM tools (Informatica/Reltio) and applying data governance best practices. Guide the team on development activities and lead the solution discussions Must have core technical capabilities in GenAI, Data Science space Good-to-Have Skills: Prior experience in Data Modeling, ETL development, and data profiling to support AI/ML workflows. Working knowledge of Life Sciences or Pharma industry standards and regulatory considerations. Proficiency in tools like JIRA and Confluence for Agile delivery and project collaboration. Familiarity with MongoDB, VectorStores, and modern architecture principles for scalable GenAI applications. Professional Certifications : Any ETL certification (e.g. Informatica) Any Data Analysis certification (SQL) Any cloud certification (AWS or AZURE) Data Science and ML Certification Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams.

ABOUT THE ROLE Role Description: We are seeking an accomplished and visionary Data Scientist/ GenAI developer to join Amgens Enterprise Data Management team. As part of MDM team, you will be responsible for design ing , develop ing , and deploy ing Generative AI and ML models to power data-driven decisions across business domains. This role is ideal for an AI practitioner who thrives in a collaborative environment and brings a strategic mindset to applying advanced AI techniques to solve real-world problems. To succeed in this role, the candidate must have strong AI/ML, Data Science , GenAI experience along with MDM knowledge, hence the candidates having only MDM experience are not eligible for this role. Candidate must have AI/ML, data science and GenAI experience on technologies like ( PySpark / PyTorch , TensorFlow, LLM , Autogen , Hugging FaceVectorDB , Embeddings, RAGs etc ), along with knowledge of MDM (Master Data Management) Roles & Responsibilities: Develop enterprise-level GenAI applications using LLM frameworks such as Langchain, Autogen, and Hugging Face. Design and develop intelligent pipelines using PySpark, TensorFlow, and PyTorch within Databricks and AWS environments. Implement embedding models andmanage VectorStores for retrieval-augmented generation (RAG) solutions. Integrate and leverage MDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems. Utilize SQL and Python for data engineering, data wrangling, and pipeline automation. Build scalable APIs and services to serve GenAI models in production. Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems. Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations. Basic Qualifications and Experience: Masters degree with 4 - 6 years of experience in Business, Engineering, IT or related field OR Bachelors degree with 6 - 9 years of experience in Business, Engineering, IT or related field OR Diploma with 10 - 12 years of experience in Business, Engineering, IT or related field Functional Skills: Must-Have Skills: 6+ years of experience working in AI/ML or Data Science roles, including designing and implementing GenAI solutions. Extensive hands-on experience with LLM frameworks and tools such as Langchain, Autogen, Hugging Face, OpenAI APIs, and embedding models. Strong programming background with Python, PySpark, and experience in building scalable solutions using TensorFlow, PyTorch, and SK-Learn. Proven track record of building and deploying AI/ML applications in cloud environments such as AWS. Expertise in developing APIs, automation pipelines, and serving GenAI models using frameworks like Django, FastAPI, and DataBricks. Solid experience integrating and managing MDM tools (Informatica/Reltio) and applying data governance best practices. Guide the team on development activities and lead the solution discussions Must have core technical capabilities in GenAI, Data Science space Good-to-Have Skills: Prior experience in Data Modeling, ETL development, and data profiling to support AI/ML workflows. Working knowledge of Life Sciences or Pharma industry standards and regulatory considerations. Proficiency in tools like JIRA and Confluence for Agile delivery and project collaboration. Familiarity with MongoDB, VectorStores, and modern architecture principles for scalable GenAI applications. Professional Certifications : Any ETL certification (e.g. Informatica) Any Data Analysis certification (SQL) Any cloud certification (AWS or AZURE) Data Science and ML Certification Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Senior Data Scientist, Operations Mumbai, India About Argus: Argus is the leading independent provider of market intelligence to the global energy and commodity markets. We offer essential price assessments, news, analytics, consulting services, data science tools and industry conferences to illuminate complex and opaque commodity markets. Headquartered in London with 1,500 staff, Argus is an independent media organisation with 30 offices in the worlds principal commodity trading hubs. Companies, trading firms and governments in 160 countries around the world trust Argus data to make decisions, analyse situations, manage risk, facilitate trading and for long-term planning. Argus prices are used as trusted benchmarks around the world for pricing transportation, commodities and energy. Founded in 1970, Argus remains a privately held UK-registered company owned by employee shareholders and global growth equity firm General Atlantic. What were looking for: Join our Generative AI team as a Senior Data Scientist, reporting directly to the Lead Data Scientist in India. You will play a crucial role in building, optimizing, and maintaining AI-ready data infrastructure for advanced Generative AI applications. Your focus will be on hands-on implementation of cutting-edge data extraction, curation, and metadata enhancement techniques for both text and numerical data. You will be a key contributor to the development of innovative solutions, ensuring rapid iteration and deployment, and supporting the Lead in achieving the team's strategic goals. What will you be doing: AI-Ready Data Development : Design, develop, and maintain high-quality AI-ready datasets, ensuring data integrity, usability, and scalability to support advanced Generative AI models. Advanced Data Processing : Drive hands-on efforts in complex data extraction, cleansing, and curation for diverse text and numerical datasets. Implement sophisticated metadata enrichment strategies to enhance data utility and accessibility for AI systems. Algorithm Implementation & Optimization : Implement and optimize state-of-the-art algorithms and pipelines for efficient data processing, feature engineering, and data transformation tailored for LLM and GenAI applications. GenAI Application Development : Apply and integrate frameworks like LangChain and Hugging Face Transformers to build modular, scalable, and robust Generative AI data pipelines and applications. Prompt Engineering Application : Apply advanced prompt engineering techniques to optimize LLM performance for specific data extraction, summarization, and generation tasks, working closely with the Lead's guidance. LLM Evaluation Support : Contribute to the systematic evaluation of Large Language Models (LLMs) outputs, analysing quality, relevance, and accuracy, and supporting the implementation of LLM-as-a-judge frameworks. Retrieval-Augmented Generation (RAG) Contribution : Actively contribute to the implementation and optimization of RAG systems, including working with embedding models, vector databases, and, where applicable, knowledge graphs, to enhance data retrieval for GenAI. Technical Mentorship : Act as a technical mentor and subject matter expert for junior data scientists, providing guidance on best practices in coding and PR reviews, data handling, and GenAI methodologies. Cross-Functional Collaboration : Collaborate effectively with global data science teams, engineering, and product stakeholders to integrate data solutions and ensure alignment with broader company objectives. Operational Excellence : Troubleshoot and resolve data-related issues promptly to minimize potential disruptions, ensuring high operational efficiency and responsiveness. Documentation & Code Quality : Produce clean, well-documented, production-grade code, adhering to best practices for version control and software engineering. Skills and Experience: Academic Background : Advanced degree in AI, statistics, mathematics, computer science, or a related field. Programming and Frameworks : 2+ years of hands-on experience with Python, TensorFlow or PyTorch, and NLP libraries such as spaCy and Hugging Face. GenAI Tools : 1+ years Practical experience with LangChain, Hugging Face Transformers, and embedding models for building GenAI applications. Prompt Engineering : Deep expertise in prompt engineering, including prompt tuning, chaining, and optimization techniques. LLM Evaluation : Experience evaluating LLM outputs, including using LLM-as-a-judge methodologies to assess quality and alignment. RAG and Knowledge Graphs : Practical understanding and experience using vector databases. In addition, familiarity with graph-based RAG architectures and the use of knowledge graphs to enhance retrieval and reasoning would be a strong plus. Cloud : 2+ years of experience with Gemini/OpenAI models and cloud platforms such as AWS, Google Cloud, or Azure. Proficient with Docker for containerization. Data Engineering : Strong understanding of data extraction, curation, metadata enrichment, and AI-ready dataset creation. Collaboration and Communication : Excellent communication skills and a collaborative mindset, with experience working across global teams. Whats in it for you: Competitive salary Hybrid Working Policy (3 days in Mumbai office/ 2 days WFH once fully inducted) Group healthcare scheme 18 days annual leave 8 days of casual leave Extensive internal and external training Hours: This is a full-time position operating under a hybrid model, with three days in the office and up to two days working remotely. The team supports Argus key business processes every day, as such you will be required to work on a shift-based rota with other members of the team supporting the business until 8pm. Typically support hours run from 11am to 8pm with each member of the team participating up to 2/3 times a week. For more details about the company and to apply please make sure you send your CV and cover letter via our website: www.argusmedia.com/en/careers/open-positions By submitting your job application, you automatically acknowledge and consent to the collection, use and/or disclosure of your personal data to the Company. Argus is an equal opportunity employer. We welcome and encourage diversity in the workplace regardless of race, gender, sexual orientation, gender identity, disability or veteran status.

Required technical and professional expertise Proof of Concept (POC) Development: Develop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another Document solution architectures, design decisions, implementation details, and lessons learned. Stay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation Preferred technical and professional experience Experience and working knowledge in COBOL & JAVA would be preferred Having experience in Code generation, code matching & code translation leveraging LLM capabilities would be a Big plus Demonstrate a growth mindset to understand clients business processes and challenges

Required technical and professional expertise Proof of Concept (POC) Development: Develop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another Document solution architectures, design decisions, implementation details, and lessons learned. Stay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation Preferred technical and professional experience Experience and working knowledge in COBOL & JAVA would be preferred Having experience in Code generation, code matching & code translation leveraging LLM capabilities would be a Big plus Demonstrate a growth mindset to understand clients business processes and challenges

Develop enterprise-level GenAI applications using LLM frameworks such as Langchain, Autogen, and Hugging Face. Design and develop intelligent pipelines using PySpark, TensorFlow, and PyTorch within Databricks and AWS environments. Implement embedding models and manage VectorStores for retrieval-augmented generation (RAG) solutions. Integrate and leverage MDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems. Utilize SQL and Python for data engineering, data wrangling, and pipeline automation. Build scalable APIs and services to serve GenAI models in production. Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems. Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations. Guide the team on development activities and lead solution discussions. Basic Qualifications and Experience: Master's degree with 4 - 6 years of experience in Business, Engineering, IT, or related field OR Bachelor's degree with 6 - 9 years of experience in Business, Engineering, IT, or related field OR Diploma with 10 - 12 years of experience in Business, Engineering, IT, or related field Functional Skills: Must-Have Skills: 6+ years of experience working in AI/ML or Data Science roles, including designing and implementing GenAI solutions. Hands-on experience with LLM frameworks and tools like Langchain, Autogen, Hugging Face, OpenAI APIs, and embedding models. Strong programming background in Python, PySpark, TensorFlow, PyTorch, and SK-Learn. Proven experience building and deploying AI/ML applications in cloud environments such as AWS. Expertise in developing APIs, automation pipelines, and serving GenAI models using Django, FastAPI, and DataBricks. Solid experience integrating and managing MDM tools (Informatica, Reltio) and applying data governance best practices. Core technical capabilities in GenAI and Data Science. Good-to-Have Skills: Experience in Data Modeling, ETL development, and data profiling to support AI/ML workflows. Knowledge of Life Sciences or Pharma industry standards and regulatory considerations. Proficiency in Agile tools like JIRA and Confluence. Familiarity with MongoDB, VectorStores, and scalable GenAI architecture principles. Professional Certifications: ETL certification (e.g., Informatica) Data Analysis certification (SQL) Cloud certification (AWS or Azure) Data Science and ML certifications Soft Skills: Strong analytical skills for assessing and improving master data processes. Excellent verbal and written communication skills for conveying complex data concepts. Effective problem-solving skills to implement scalable solutions. Ability to work effectively with global and virtual teams.

We are seeking an accomplished and visionary Data Scientist/ GenAI Lead to join Amgen's Enterprise Data Management team. As MDM Data Science/Manager, you will lead the design, development, and deployment of Generative AI and ML models to power data-driven decisions across business domains. This role is ideal for an AI practitioner who thrives in a collaborative environment and brings a strategic mindset to applying advanced AI techniques to solve real-world problems. Key Responsibilities: Drive development of enterprise-level GenAI applications using LLM frameworks such as Langchain, Autogen, and Hugging Face. Architect intelligent pipelines using PySpark, TensorFlow, and PyTorch within Databricks and AWS environments. Implement embedding models and manage VectorStores for retrieval-augmented generation (RAG) solutions. Integrate and leverage MDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems. Utilize SQL and Python for data engineering, data wrangling, and pipeline automation. Build scalable APIs and services to serve GenAI models in production. Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems. Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations.

Job Description Join our team as a Generative AI Architect in the AI Practice! We are looking for a visionary individual to lead the design, development, and deployment of cutting-edge Generative AI solutions, driving business value across our products and services. Key Responsibilities: - Lead generative AI initiatives in text, ASR, TTS & STT generation and develop AI pipelines and ML models. - Design scalable AI systems using state-of-the-art generative models like LLMs and diffusion models. - Collaborate with cross-functional teams to integrate generative AI into business workflows. - Define best practices for model lifecycle management, focusing on data preparation, training, evaluation, deployment, and monitoring. - Guide ethical AI development with a focus on fairness, interpretability, and compliance. Qualifications: - Bachelors or Masters degree in Computer Science or related field. - 7+ years of AI/ML development experience, with 2+ years in generative AI. - Hands-on experience with large language models and diffusion models. - Strong proficiency in Python and ML frameworks. - Experience with Azure, GCP, and containerization. - Familiarity with AI architecture patterns and model fine-tuning. - Knowledge of data privacy laws and AI ethics principles. Preferred: - Experience deploying GenAI applications in production. - Knowledge of vector databases and retrieval-augmented generation. - Experience with CI/CD pipelines for ML. Skills : - Generative AI,Large Language Models (LLMs),Diffusion Models,Machine Learning (ML),Artificial Intelligence (AI),Natural Language Processing (NLP),Python Programming,ML Frameworks (e.g., TensorFlow, PyTorch, Hugging Face),Azure,GCP,Ethical AI,Responsible AI,Vector Databases, RAG

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

Introduction A career in IBM Software means youll be part of a team that transforms our customers challenges into solutions. Seeking new possibilities and always staying curious, we are a team dedicated to creating the worlds leading AI-powered, cloud-native software solutions for our customers. Our renowned legacy creates endless global opportunities for our IBMers, so the door is always open for those who want to grow their career. IBMs product and technology landscape includes Research, Software, and Infrastructure. Entering this domain positions you at the heart of IBM, where growth and innovation thrive Your role and responsibilities We are seeking an experienced and innovative AI Solution Engineer to be specialized in foundation models and large language models. In this role, you will be responsible for architecting and delivering AI and Automation solutions using cutting-edge technologies, with a strong focus on foundation models and large language models. In this role, you will be resposible for : .Proof of Concept (POC) Development: Develop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. .Customer Engagement and Support: Act as a technical point of contact for customers, addressing their questions, concerns, and feedback. Provide technical support during the solution deployment phase and offer guidance on AI-related best practices and use cases. .Industry Trends and Innovation: Stay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation. Required education Bachelors Degree Preferred education Masters Degree Required technical and professional expertise .Bachelors or Masters degree in Computer Science, Artificial Intelligence, or a related field. .4+ years of experience in designing and delivering AI solutions, with a focus on foundation models, large language models, or similar technologies. Experience in natural language processing (NLP) and text analytics is highly desirable. .Technical Skills: Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and related services is a plus. .Solutioning Experience: Experience in solution architecture and design, translating business requirements into technical specifications, and developing scalable and robust AI solutions. .Business Acumen: Ability to understand customer needs and business objectives. Experience in working closely with customers and translating their requirements into effective AI solutions. .Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI. .Growth mindset: Demonstrate a growth mindset to understand clients business processes and cha Preferred technical and professional experience .Experience in full AI project lifecycle, from research and prototyping to deployment in production environments. .Familiarity with Agile development methodologies .Experience with AI and/or data governance .Experience with building business automation or digital labor solutions .Experience with building customer care solutions/digital assistants .Experience with Red Hat OpenShift .Experience with Kubernetes .Experience with vector DBs or open file formats like parquet ,avro or orc

About the Role We are looking for a Senior Data Scientist to come and work on our growing AI stack. You will be working with a team of highly skilled and motivated data scientists and machine learning engineers. If you are excited about natural language understanding and machine translation, AppZen is the right place for you to apply and grow your skills. Key Responsibilities: Solid understanding of machine learning fundamentals, and familiar with standard algorithms and techniques Solid understanding of Python programming, including core data structures (lists, dicts, sets, tuples), object-oriented design, and writing clean, modular, and maintainable code. Experience with code optimization techniques, including efficient memory and runtime usage, vectorization (NumPy/Pandas), and debugging performance bottlenecks. Hands-on experience with LLMs such as GPT, LLaMA, or Claude, including evaluation and integration into production pipelines. Proficiency in using GenAI frameworks and tools (e.g., Hugging Face Transformers, LangChain, OpenAI APIs, vLLM, or AutoGen) to build, customize, and deploy language-based solutions. Ability to analyze, evaluate, and optimize LLM outputs for accuracy, safety, relevance, and bias mitigation in enterprise use cases. Work with internal and external stakeholders on program management Manage your own process: identify and execute on high impact projects, triage external requests, and make sure you bring projects to conclusion in time for the results to be useful Excellent written and verbal technical communication skills; communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions M.Tech/B.Tech. or equivalent experience in Computer Science, Engineering, Statistics, or other relevant technical field Must have 6+ years of industry experience You are a team player Nice-to-Have: Track record of having developed novel algorithms, e.g. publications in one or more of the following: KDD, WWW, NIPS, ISWC, NAACL, ACL, SIGIR, EMNLP, ICML etc Good Understanding of MLOps tools/processes like ElasticSearch, Jenkins, Docker is plus. Expertise in building and fine-tuning LLM models using Transformers and RAG systems.

Job Title: ML Prompt Engineer Location - Bangalore Hybrid . Job Description: Principle Developer - ML/Prompt Engineer Technologies: Amazon Bedrock, RAG Models, Java, Python, C or C++, AWS Lambda Responsibilities: Responsible for developing, deploying, and maintaining a Retrieval Augmented Generation (RAG) model in Amazon Bedrock, our cloud-based platform for building and scaling generative AI applications. Design and implement a RAG model that can generate natural language responses, commands, and actions based on user queries and context, using the Anthropic Claude model as the backbone. Integrate the RAG model with Amazon Bedrock, our platform that offers a choice of high-performing foundation models from leading AI companies and Amazon via a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI. Optimize the RAG model for performance, scalability, and reliability, using best practices and robust engineering methodologies. Design, test, and optimize prompts to improve performance, accuracy, and alignment of large language models across diverse use cases. Develop and maintain reusable prompt templates, chains, and libraries to support scalable and consistent GenAI applications. Skills/Qualifications: Experience in programming with at least one software language, such as Java, Python, or C/C++. Experience in working with generative AI tools, models, and frameworks, such as Anthropic, OpenAI, Hugging Face, TensorFlow, PyTorch, or Jupyter. Experience in working with RAG models or similar architectures, such as RAG, Ragna, or Pinecone. Experience in working with Amazon Bedrock or similar platforms, such as AWS Lambda, Amazon SageMaker, or Amazon Comprehend. Ability to design, iterate, and optimize prompts for various LLM use cases (e.g., summarization, classification, translation, Q&A, and agent workflows). Deep understanding of prompt engineering techniques (zero-shot, few-shot, chain-of-thought, etc.) and their effect on model behavior. Familiarity with prompt evaluation strategies, including manual review, automatic metrics, and A/B testing frameworks. Experience building prompt libraries, reusable templates, and structured prompt workflows for scalable GenAI applications. Ability to debug and refine prompts to improve accuracy, safety, and alignment with business objectives. Awareness of prompt injection risks and experience implementing mitigation strategies. Familiarity with prompt tuning, parameter-efficient fine-tuning (PEFT), and prompt chaining methods. Familiarity with continuous deployment and DevOps tools preferred. Experience with Git preferred Experience working in agile/scrum environments Successful track record interfacing and communicating effectively across cross-functional teams. Good communication, analytical and presentation skills, problem-solving skills and learning attitude

Position Summary: We value our talented employees, and whenever possible strive to help one of our associates grow professionally before recruiting new talent to our open positions. If you think the open position you see is right for you, we encourage you to apply! Our people make all the difference in our success. We leverage cutting edge Artificial Intelligence (AI) and Machine Learning (ML) algorithms to develop solutions for automated document processing and customer service chat bots. We are looking for AI Prompt Engineers with strong engineering, full stack expertise to build the best fit solutions leveraging Large Language Models (LLMs) and Generative AI solutions. Extreme focus on speed to market and getting Products and Services in the hands of customer and passion to transform healthcare is key to the success of this role. Build scalable software solutions using LLMs and other ML models to solve challenges in healthcare. Build enterprise grade AI solutions with focus on privacy, security, fairness. Work with Product Development as a Generative Artificial Intelligence (AI) subject matter expert and architect and develop scalable, resilient, ethical AI solutions Strong engineering skills to design the output from the AI with nodes and nested nodes in JSON or array, HTML formats as required This is critical so that the AI output can be consumed as is and displayed on the dashboard for accelerated development cycles. Build extensible API Integrations, low code UI UX solutions, with extremely short cycle times, to extract information from sources, integrate with GPT4, receive insights and make them available in intuitive, high performing dashboards Build solutions that align with responsible AI practices. Envision the solution outcomes to solve for the business problem with actionable insights and design viable solutions to meet the outcomes. Understand how AI is interpreting the data set and use that understanding to build prompts that lead to expected outcomes Architect and develop software or infrastructure for scalable, distributed systems and with machine learning technologies. Work with frameworks(Tensorflow, PyTorch) and open source platforms like Hugging Face to deliver the best solutions Optimize existing generative AI models for improved performance, scalability, and efficiency. Develop and maintain AI pipelines, including data preprocessing, feature extraction, model training, and evaluation. Develop clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders. Contribute to the establishment of best practices and standards for generative AI development within the organization. Experience Required: Overall 3+ years of experience 3 years of Full stack engineering expertise with languages like C#, Python and Proficiency in designing architecture, building API Integrations, configuring and deploying cloud services, setting up authentication, monitoring and logging Experience in implementing enterprise systems in production setting for AI, computer vision, natural language processing. Exposure to self-supervised learning, transfer learning, and reinforcement learning is a plus. Experience with information storage/retrieval using vector databases like pinecone. Strong understanding and exposure in natural language generation or Gen AI like transformers, LLMs, text embeddings. Experience with designing scalable software systems for classification, text extraction/summary, data connectors for different formats (pdf, csv, doc, etc) Experience with machine learning libraries and frameworks such as PyTorch or TensorFlow, Hugging Face, Lang chain, Llama Index. 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects. Programming experience in C C++, Java, Python. Strong knowledge of data structures, algorithms, and software engineering principles. Excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions. Strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience. Possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Experience Desired: Familiarity with cloud-based platforms and services, such as AWS, GCP, or Azure. Hands on experience on tools products like Dynatrace, Splunk, Service Now preferred. Experience in identifying KPI on solution build using Generative AI, for Ex RAG based Q&A, data summarization, text content generation, data extraction, etc. will be a big advantage. Understanding of standards and regulation related to use of GenAI for a US based Health Insurance provider preferred. Healthcare experience (preferred but not mandate) Education and Training Required: Degree in Computer Science, Artificial Intelligence, or a related field.

Overview We are seeking an experienced Reporting GenAI Consultant with a strong background in developing AI-driven reporting solutions. This role focuses on building and integrating Generative AI capabilities into BI platforms to enable natural language insights, automated report generation, and interactive dialogue with data. The ideal candidate will have hands-on experience working with LLMs, prompt engineering, and modern data visualization tools. Responsibilities Design, develop, and deploy GenAI-based reporting solutions that generate insights summaries, dashboards, and narrative analytics using structured and unstructured data. Build natural language interfaces and conversational agents for querying data (Dialogue with Data), enabling users to interact with reports through plain English. Integrate GenAI features (like ChatGPT, Azure OpenAI, or Vertex AI) with enterprise BI platforms (Power BI, Tableau, Qlik, ThoughtSpot, etc.). Implement automated insight generation using LLMs to summarize trends, detect anomalies, and generate key takeaways. Collaborate with data engineering and BI teams to optimize data models and ensure clean, prompt-ready datasets. Design and fine-tune prompts and templates for contextual report summarization and storytelling . Conduct POCs and pilots to evaluate the feasibility and impact of GenAI-driven reporting use cases. Ensure solutions are secure, scalable, and compliant with enterprise governance policies. Qualifications 10+ years of experience in Business Intelligence / Analytics with 12 years in Generative AI implementations . Strong experience in Power BI with exposure to augmented analytics features. Experience working with LLMs (OpenAI, Azure OpenAI, Hugging Face, Google PaLM, etc.) for natural language understanding and summarization. Expertise in prompt engineering , few-shot learning, and custom summarization models. Good understanding of data storytelling , narrative generation , and auto-generated insights . Experience in integrating APIs for AI models into web or reporting tools. Familiarity with Python or JavaScript for model integration and backend logic. Excellent communication and stakeholder management skills. Preferred Qualifications: Experience with RAG (Retrieval-Augmented Generation) , LangChain , or similar frameworks. Exposure to voice-based analytics or speech-to-insight solutions. Knowledge of data governance, privacy (GDPR/CPRA) , and enterprise security standards . Familiarity with cloud platforms : Azure.