118 Hugging Face Jobs - Page 5

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.

Hiring AI & Data Retrieval Engineer with expertise in NLQ, Text-to-SQL, LLMs, LangChain, pgVector, PostgreSQL, vector search, Python, AI libraries, Agentic AI & API integration. Exp with NLP, RAG, BI tools, live projects & LLM fine-tuning preferred.

Senior Technical Architect Machine Learning Solutions We are looking for a Senior Technical Architect with deep expertise in Machine Learning (ML), Artificial Intelligence (AI) , and scalable ML system design . This role will focus on leading the end-to-end architecture of advanced ML-driven platforms, delivering impactful, production-grade AI solutions across the enterprise. Key Responsibilities Lead the architecture and design of enterprise-grade ML platforms , including data pipelines, model training pipelines, model inference services, and monitoring frameworks. Architect and optimize ML lifecycle management systems (MLOps) to support scalable, reproducible, and secure deployment of ML models in production. Design and implement retrieval-augmented generation (RAG) systems, vector databases , semantic search , and LLM orchestration frameworks (e.g., LangChain, Autogen). Define and enforce best practices in model development, versioning, CI/CD pipelines , model drift detection, retraining, and rollback mechanisms. Build robust pipelines for data ingestion, preprocessing, feature engineering , and model training at scale , using batch and real-time streaming architectures. Architect multi-modal ML solutions involving NLP, computer vision, time-series, or structured data use cases. Collaborate with data scientists, ML engineers, DevOps, and product teams to convert research prototypes into scalable production services . Implement observability for ML models including custom metrics, performance monitoring, and explainability (XAI) tooling. Evaluate and integrate third-party LLMs (e.g., OpenAI, Claude, Cohere) or open-source models (e.g., LLaMA, Mistral) as part of intelligent application design. Create architectural blueprints and reference implementations for LLM APIs, model hosting, fine-tuning, and embedding pipelines . Guide the selection of compute frameworks (GPUs, TPUs), model serving frameworks (e.g., TorchServe, Triton, BentoML) , and scalable inference strategies (batch, real-time, streaming). Drive AI governance and responsible AI practices including auditability, compliance, bias mitigation, and data protection. Stay up to date on the latest developments in ML frameworks, foundation models, model compression, distillation, and efficient inference . 14. Ability to coach and lead technical teams , fostering growth, knowledge sharing, and technical excellence in AI/ML domains. Experience managing the technical roadmap for AI-powered products , documentations ensuring timely delivery, performance optimization, and stakeholder alignment. Required Qualifications Bachelors or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 8+ years of experience in software architecture , with 5+ years focused specifically on machine learning systems and 2 years in leading team. Proven expertise in designing and deploying ML systems at scale , across cloud and hybrid environments. Strong hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face, Scikit-learn). Experience with vector databases (e.g., FAISS, Pinecone, Weaviate, Qdrant) and embedding models (e.g., SBERT, OpenAI, Cohere). Demonstrated proficiency in MLOps tools and platforms : MLflow, Kubeflow, SageMaker, Vertex AI, DataBricks, Airflow, etc. In-depth knowledge of cloud AI/ML services on AWS, Azure, or GCP – including certification(s) in one or more platforms. Experience with containerization and orchestration (Docker, Kubernetes) for model packaging and deployment. Ability to design LLM-based systems , including hybrid models (open-source + proprietary), fine-tuning strategies, and prompt engineering. Solid understanding of security, compliance , and AI risk management in ML deployments. Preferred Skills Experience with AutoML , hyperparameter tuning, model selection, and experiment tracking. Knowledge of LLM tuning techniques : LoRA, PEFT, quantization, distillation, and RLHF. Knowledge of privacy-preserving ML techniques , federated learning, and homomorphic encryption Familiarity with zero-shot, few-shot learning , and retrieval-enhanced inference pipelines. Contributions to open-source ML tools or libraries. Experience deploying AI copilots, agents, or assistants using orchestration frameworks.

Seeking a highly skilled and motivated Senior Generative AI Developer with approximately 2 years of hands-on experience in developing and deploying AI models, particularly in the generative space (e.g., NLP, AL/ML, AWS, Python, RASA, MCP, Flutter). Required Candidate profile 2+ yrs of exp in AI/ML dev, with focus on gen models. Prog skills in Python & ML libraries/frameworks Langchain, spacy, NLTK, Hugging Face Exp in AI bot/agent platforms like Make, POE, RetellAI

In this role you will: Develop and fine-tune LLMs for contract analysis, regulatory classification, and risk assessment. Implement Retrieval-Augmented Generation (RAG) using vector embeddings and hybrid DB-based querying to power DPIA and compliance workflows. Build AI-driven contract analysis systems to detect dark patterns, classify clauses, and provide remediation suggestions. Develop knowledge graph-based purpose taxonomies for privacy policies and PII classification. Automate data discovery for structured and unstructured data, classifying it into PII categories. Optimize sliding window chunking, token-efficient parsing, and context-aware summarization for legal and compliance texts. Build APIs and ML services for deploying models in a high-availability production environment. Collaborate with privacy, legal, and compliance teams to build AI solutions that power Privy s data governance tools. Stay ahead of the curve with agentic RAG, multi-modal LLMs, and self-improving models in the compliance domain. Skills Required: LLM , RAG , AgenticAI , NLP , Python , Problem solving Candidate Attributes: Must-Have Skills 3-5 years of experience in Machine Learning, NLP, and LLM-based solutions. Strong expertise in fine-tuning and deploying LLMs (GPT-4, Llama, Mistral, or custom models). Experience with RAG-based architectures, including vector embeddings (FAISS, ChromaDB, Weaviate, Pinecone, or similar). Hands-on with agentic RAG, sliding window chunking, and efficient context retrieval techniques. Deep understanding of privacy AI use cases, including contract analysis, regulatory classification, and PII mapping. Proficiency in Python and frameworks like PyTorch, TensorFlow, JAX, Hugging Face, or LangChain. Experience in building scalable AI APIs and microservices. Exposure to MLOps practices, including model monitoring, inference optimization, and API scalability. Experience working with at least one cloud provider (AWS, GCP, or Azure). Good-to-Have Skills Experience in hybrid AI architectures combining vector search + relational databases. Familiarity with functional programming languages (Go, Elixir, Rust, etc.). Understanding of privacy compliance frameworks (DPDP Act, GDPR, CCPA, ISO 27701). Exposure to Kubernetes, Docker, and ML deployment best practices. Contributions to open-source LLM projects or privacy AI research.

Hello, Urgent job openings for Data Science(Gen AI & LLM) :- Team Lead/ Sr Engineer @ GlobalData(Hyd). Looking for candidates with experience in Gen AI, LLM, RAG frameworks Job Description given below please go through to understand the requirement. if requirement is matching to your profile share your updated resume @ mail id (m.salim@globaldata.com). Mention Subject Line :- Applying for Data Science(Gen AI/LLM) - Lead/SSE @ GlobalData(Hyd) Share your details in the mail :- Full Name : Mobile # : Qualification : Company Name : Designation : Total Work Experience Years : Current CTC : Expected CTC : Notice Period : Current Location/willing to relocate to Hyd? : Office Address : 3rd Floor, Jyoti Pinnacle Building, Opp to Prestige IVY League Appt, Kondapur Road, Hyderabad, Telangana-500081. Job Description: Senior Engineer/Lead - Gen AI/LLM Position Overview:- We are seeking a talented Lead/Senior Engineer AI/LLM Developer to join our team and drive the development of cutting-edge artificial intelligence solutions using large language models. In this role, you will design, build, and optimize LLM-based applications that solve complex business problems while maintaining high standards of performance, scalability, and reliability. Key Responsibilities:- Design and implement sophisticated AI applications leveraging state-of-the-art LLM technologies Develop efficient solutions for LLM integration, fine-tuning, and deployment Optimize model performance, latency, and resource utilization Build and maintain robust data pipelines for training and inference Implement advanced prompt engineering techniques and retrieval-augmented generation (RAG) Develop evaluation frameworks to measure AI system performance and output quality Collaborate with cross-functional teams to understand requirements and deliver solutions Mentor junior developers and share AI/LLM knowledge across the organization Participate in code reviews and ensure adherence to best practices Role Requirement :- 5+ years of software development experience with at least 3 years focused on AI/ML technologies Strong experience working with transformer-based models and LLM APIs Proficiency in Python and relevant AI/ML frameworks (PyTorch, TensorFlow, Hugging Face) Experience with vector databases and semantic search technologies Solid understanding of prompt engineering, RAG, and fine-tuning techniques Familiarity with cloud platforms (AWS, Azure, GCP) for AI model deployment Strong problem-solving skills and attention to detail.' Experience with LLM optimization techniques like quantization and distillation Knowledge of AI evaluation metrics and benchmarking methodologies Understanding of multimodal AI systems (text, image, audio) Experience with containerization and orchestration tools (Docker, Kubernetes) Contributions to open-source AI projects or research publications Familiarity with AI ethics and responsible AI development Qualifications:- Bachelors degree in computer science, AI, Machine Learning, or related field Master's in AI, B,Tech,MCA, or related field Thanks & Regards, Salim (Human Resources)

Looking for a highly motivated, self-driven AI Experienced Data Scientist for building differentiating solutions and for implementing AI and Generative AI (Gen AI) based solutions for customer's business problems. As an AI Solution Engineer , build AI and Gen AI empowered practical in-depth solutions for solving customers business problems. As an AI and Data Solution Engineer , design and implement Cloud Data, AI, and Gen AI based solutions , including LLM-powered systems, for customer programs. Apply statistics, modeling, LLMs , and machine learning to improve the efficiency of systems and relevance algorithms across our business application products. Requirements Bachelors degree or Masters degree in Computer Science / AIML / Data Science. 4 to 6 years of overall experience and hands-on experience with the design and implementation of Machine Learning models, Deep Learning models, and Gen AI models (e.g., GPT, LLaMA, Mistral) for solving business problems. Proven experience working with Generative AI technologies , including prompt engineering, fine-tuning large language models (LLMs), embeddings, vector databases (e.g., FAISS, Pinecone), and Retrieval-Augmented Generation (RAG) systems. Expertise in R, Python (NumPy, Scikit-learn, Pandas), TensorFlow, PyTorch, transformers (e.g., Hugging Face) , or MLlib. Expertise in cloud-based data and AI solution design and implementation using GCP / AWS / Azure , including the use of their Gen AI services. Good experience in building complex and scalable ML and Gen AI solutions and deploying them into production environments. Experience with scripting in SQL, extracting large datasets, and designing ETL flows. Excellent problem-solving and analytical skills with the ability to translate business requirements into data science and Gen AI solutions. Effective communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders.

We are seeking an experienced and innovative AI Specialist to join our dynamic team. The ideal candidate will possess deep expertise in artificial intelligence, machine learning, and neural networks, with a proven track record of designing, developing, and deploying AI solutions. The candidate should be adept at analyzing large datasets, developing optimized algorithms, and integrating AI models into production environments. This role offers the opportunity to contribute to cutting-edge AI applications that solve real-world problems and drive business value Key Responsibilities: AI System Design & Development: Design, develop, and implement AI systems and applications, including machine learning models, neural networks, and natural language processing (NLP) algorithms. Create and optimize AI algorithms for tasks such as image recognition, speech processing, and predictive analytics. Data Analysis & Feature Engineering: Analyze large datasets to identify trends, patterns, and actionable insights. Perform data preprocessing, data wrangling, and feature engineering to enhance model performance. Model Training & Optimization: Train and fine-tune machine learning models using labeled and unlabeled data to improve model accuracy and efficiency. Continuously monitor and optimize models for better performance. AI Model Integration: Deploy machine learning models into production environments, ensuring scalability and reliability. Integrate AI technologies with existing software and business processes using REST APIs. Utilize Docker and Kubernetes to containerize and manage AI models. Research & Innovation: Stay up to date with the latest advancements in AI and machine learning technologies. Explore and experiment with new AI applications, tools, and methodologies to enhance system capabilities. Collaboration & Agile Development: Work closely with cross-functional teams in an Agile environment to develop AI-driven solutions that meet business requirements. Communicate findings and results to stakeholders, ensuring AI solutions align with business goals. Primary Skills and Qualifications: AI and Machine Learning Expertise: Strong knowledge of supervised and unsupervised learning techniques, including classification, regression, clustering, and reinforcement learning. Hands-on experience developing and deploying machine learning models in production environments. Technical Proficiency: Programming Languages: Advanced proficiency in Python, with additional experience in R and SQL as a plus. ML Libraries/Frameworks: Expertise in TensorFlow, PyTorch, and scikit-learn. Cloud Platforms: Hands-on experience with AWS, Azure, or Google Cloud for model deployment and management. Model Deployment & Integration: Familiarity with REST APIs, Docker, and Kubernetes for seamless model integration. Secondary Skills and Preferred Qualifications: Natural Language Processing (NLP): Experience with NLP frameworks such as NLTK, spaCy, Hugging Face, and BERT. Agile Methodologies: Knowledge of Agile practices, with experience using tools like JIRA for project management. Mathematics and Statistics: Strong foundation in probability, statistics, and linear algebra to support model development and evaluation. Data Handling & Preprocessing: Proficiency in data cleaning, transformation, and feature engineering to prepare data for modeling.

Develop and deploy AI-based applications leveraging LLMs and Generative AI models like GPT, Gemini, or similar frameworks Build scalable backend systems using Python, ensuring seamless integration with UI/UX components Design and optimize generative AI models to address diverse business challenges Fine-tune pre-trained LLMs to align with specific use cases Work closely with cross-functional teams, including data scientists, UI/UX developers, and product managers, to deliver robust solutions Collaborate with clients to gather requirements and develop customized AI capabilities Deploy solutions on cloud platforms (Azure, AWS, or GCP) and ensure system scalability and performance