299 Hugging Face Jobs - Page 6

As a Developer Specialist AI, Full-Stack at DN Nagar, Andheri West, Mumbai, you will play a crucial role in combining hands-on coding expertise with a strong understanding of system design, API integration, and AI-driven workflows. Your responsibilities will involve working across the entire tech stack, including frontend, backend, databases, AI frameworks, and cloud infrastructure, to develop robust, scalable, and intelligent systems. This role requires more than just writing code; you will be accountable for designing solutions, integrating various technologies, and creating efficient, reliable, and future-ready end-to-end workflows. Your key responsibilities will include architecting, developing, and integrating AI-driven systems and applications, designing and implementing scalable workflows connecting multiple technologies, leading API development and integration for data extraction, processing, and automation, developing modern frontend applications using React.js, building and optimizing backend services with FastAPI or Node.js, implementing and managing database solutions such as PostgreSQL, Elasticsearch, Pinecone, or similar vector databases, leveraging AI frameworks like ChatGPT, Claude, TensorFlow, PyTorch, Hugging Face for building intelligent applications, driving automation processes using tools like Selenium, Scrapy, or Playwright, deploying and managing solutions on Azure, AWS, or GCP, creating and maintaining documentation to ensure code quality and scalability, and collaborating with cross-functional teams to deliver data-driven solutions, dashboards, and visualizations for media metrics and PR reporting. The ideal candidate for this role will have 3-4 years of professional development experience with exposure to full-stack development and AI/ML technologies, proven expertise with AI frameworks including LLMs, TensorFlow, PyTorch, or Hugging Face, strong API development and integration skills, solid experience with web scraping using tools like Selenium, Scrapy, or Playwright, proficiency in React.js, FastAPI/Node.js, and relational as well as vector databases, experience in building AI pipelines and automation workflows, a strong understanding of system design principles, experience with cloud deployments on Azure, AWS, or GCP, the ability to work in a fast-paced environment with minimal supervision, and excellent communication skills with a collaborative mindset. To apply for this position, please send your CV and portfolio to hr@madchatter.in with the subject line "Developer Specialist - Immediate Joiner".,

We are looking for a highly skilled Senior MERN Full Stack Developer with expertise in AI Prompt Engineering to join our dynamic team. In this role, you will be responsible for building scalable, high-performance web applications using the MERN stack (MongoDB / PostgreSQL, MySQL, Express.js, React.js, Node.js) and integrating advanced AI features into products through prompt engineering for models like GPT and BERT. With 4-7 years of experience, you should have strong technical skills in MERN Stack, including MongoDB / PostgreSQL, MySQL, Express.js, React.js, Node.js, as well as expertise in JavaScript/TypeScript, asynchronous and functional programming, RESTful APIs, and WebSockets. Experience with AI models like GPT, BERT, TensorFlow, PyTorch, OpenAI API, and Hugging Face is also required. Additionally, you should be proficient in MongoDB and relational databases (PostgreSQL, MySQL). Soft skills such as problem-solving, communication, and leadership are essential, along with the ability to mentor and guide junior developers. You should be adaptable to new technologies and practices. Your key responsibilities will include designing, developing, and maintaining full-stack applications, collaborating with cross-functional teams, implementing RESTful APIs, optimizing performance, and ensuring cross-platform responsiveness. You will also work on developing AI-driven features using prompt engineering for language models, fine-tuning models for automation, chatbots, and recommendation systems, as well as leading, mentoring, and reviewing code for junior and mid-level developers. Participation in sprint planning, project scoping, risk mitigation, and ensuring timely delivery of features will be part of your project management responsibilities. We offer a competitive salary and benefits package, the opportunity to work in a collaborative and innovative environment, professional growth and skill development, and the potential to lead a group of developers in the future. Join Brilyant and become part of a high-performing team that is shaping the future of IT solutions.,

You are seeking an AI Engineer (Level 2 & 3) with a deep passion for exploring AI technologies, particularly Large Language Models (LLMs) and advanced NLP techniques. The ideal candidate will have a strong foundation in deep learning architectures and experience with state-of-the-art AI frameworks. In this role, you will work on developing and deploying intelligent applications that solve real-world problems for our clients, leveraging tools like LangChain, Hugging Face, and OpenAI APIs. Your responsibilities will include designing and developing AI solutions focusing on large language models, experimenting with state-of-the-art Transformer architectures to address complex language understanding and generation tasks. You will leverage modern AI frameworks and tools to develop, fine-tune, and integrate LLMs into applications, ensuring models are optimized and efficient for production use. Implement and enhance NLP capabilities like text generation, summarization, and retrieval-augmented generation (RAG) to provide intelligent and contextually aware features in solutions. Craft effective prompts and fine-tune LLMs to improve model performance for specific domains and use cases. Deploy and scale models in production environments, implementing MLOps best practices for robust, repeatable model deployments. Utilize cloud services for model training, deployment, and infrastructure management, optimizing resources to handle large-scale training and inference efficiently. Continuously optimize model performance and implement scaling strategies to handle large datasets and high-volume usage. Collaborate with cross-functional teams to integrate AI capabilities into products, ensuring AI systems meet client needs and quality standards. Stay up-to-date with the latest AI research, papers, and trends in the industry, experimenting with new algorithms, models, and techniques to keep solutions at the cutting edge. You should have a Bachelor's or Master's degree in Computer Science, Engineering, or a related field, plus 4+ years of hands-on experience in AI/ML engineering or a similar role. Strong foundation in deep learning and NLP, experience in transformer-based architectures and large language models is required. Proficiency in Python programming and experience with major AI/ML frameworks and libraries is necessary. Proven experience in developing NLP solutions, model tuning, deployment of machine learning models, and familiarity with deploying in cloud environments is highly desired.,

You are a senior professional with at least 6+ years of hands-on experience in Python focusing on AI technologies. Your proficiency lies in Python and you have worked with libraries such as NumPy, Pandas, scikit-learn, TensorFlow, or PyTorch. Your expertise includes a solid understanding of machine learning algorithms, model evaluation, and data preprocessing techniques. You have experience dealing with both structured and unstructured data sets. Additionally, you are familiar with version control systems like Git and collaborative development practices. Your strong problem-solving skills enable you to work effectively both independently and as part of a team. Desired Skills: - You have experience in natural language processing (NLP), computer vision, or time-series forecasting. - You are familiar with MLOps tools and practices for model deployment and monitoring. - Your background includes working with Generative AI models such as GPT, LLaMA, or Stable Diffusion. - You have knowledge of prompt engineering, fine-tuning, or embedding techniques for large language models (LLMs). - Hands-on experience with LLM frameworks like LangChain, Haystack, or Transformers (Hugging Face) is a plus. - You understand vector databases (e.g., Postgres, Pinecone) for retrieval-augmented generation (RAG) pipelines. - Any contributions to open-source AI/ML projects or published research would be beneficial. Locations: Hyderabad / Chennai / Bangalore / Pune. If you meet the above criteria and are interested in this opportunity, please share your resume at hr@neev.global or call 9429691736. This is a full-time position that requires you to work in person.,

The primary responsibility of this role involves designing, developing, and implementing generative AI models and algorithms using cutting-edge techniques like GPT, VAE, and GANs. You will collaborate with cross-functional teams to define project requirements in line with business goals. Staying updated with the latest advancements in generative AI, machine learning, and deep learning is crucial for identifying opportunities to enhance our products and services. Additionally, you will be optimizing existing AI models for better performance, scalability, and efficiency. Developing and maintaining AI pipelines, including data preprocessing, feature extraction, model training, and evaluation, is also a key aspect of this role. Clear and concise documentation will be essential to communicate complex AI concepts to both technical and non-technical stakeholders. Furthermore, you will contribute to establishing best practices and standards for generative AI development within the organization. Providing technical mentorship and guidance to junior team members, ensuring trusted AI practices, and driving DevOps and MLOps practices are also part of the responsibilities. Utilizing tools like Docker, Kubernetes, and Git for building and managing AI pipelines, implementing monitoring and logging tools for AI model performance and reliability, and collaborating seamlessly with software engineering and operations teams for efficient AI model integration and deployment are essential tasks. Familiarity with DevOps and MLOps practices, continuous integration, deployment, and monitoring of AI models will be advantageous. The ideal candidate for this role should have a minimum of 5 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques is required. Proficiency in programming languages like Python, R, and frameworks such as TensorFlow or PyTorch is essential. A strong understanding of NLP techniques and frameworks like BERT, GPT, or Transformer models is necessary. Familiarity with computer vision techniques, cloud platforms like Azure or AWS, data engineering, and trusted AI practices is also crucial. Strong collaboration skills with software engineering and operations teams, problem-solving abilities, and the capability to translate business requirements into technical solutions are key qualifications for this role. Excellent communication and interpersonal skills, along with a track record of driving innovation and staying updated with the latest AI research and advancements, are essential. A degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field is required, with a Master's degree preferred. Solid experience in developing and implementing generative AI models, proficiency in Python, experience with machine learning libraries and frameworks, strong knowledge of data structures, algorithms, and software engineering principles, familiarity with cloud-based platforms, and experience with NLP techniques and tools are also desired qualifications for this position.,

As a Generative AI Specialist, you will be responsible for developing GenAI LLM model-driven solutions using state-of-the-art models such as OpenAI, Gemini, and Claude, as well as open-source models like Llama and Mistral. Your main role will involve fine-tuning and training models, with a focus on implementing projects involving Agents, Tools, and RAG solutions. You should have hands-on experience in integrating LLMs with VectorDBs like Chromadb, Faiss, and Pinecone. To excel in this role, you must demonstrate expertise in PEFT, quantization of models, and have experience working with tools such as Tensorflow, Pytorch, Python, Hugging Face, and Transformers. Proficiency in data preparation, analysis, and deep learning model development is highly preferred. Additionally, familiarity with deploying models in AWS is desired but not mandatory. Key skills for this role include OpenAI, Gemini, LangChain, Transformers, Hugging Face, Python, Pytorch, Tensorflow, VectorDBs (Chromadb, Faiss, Pinecone). You should have a track record of at least 1-2 live implementations of Generative AI-driven solutions, with extensive experience in deploying chatbots, knowledge search, and NLP solutions. A solid background in implementing machine learning and deep learning solutions for a minimum of 2 years is also expected. This position is based in Chennai, with the work shift from 11 AM to 8 PM. The mode of work is from the office, and the office address is 4th Floor, Techno Park, 10, Rajiv Gandhi Salai, Customs Colony, Sakthi Nagar, Thoraipakkam, Chennai 600097.,

As a Generative AI/ML Python Developer with 3 to 5 years of experience, you will be responsible for building and deploying generative and traditional ML models from ideation and data preparation to production pipelines and performance optimization. Your role will involve solving real problems, handling data end-to-end, navigating the AI development lifecycle, and contributing to model innovation and operational excellence. Your key responsibilities will include engaging in the full AI/ML lifecycle, building and fine-tuning transformer-based LLMs (like GPT, BERT), GANs, diffusion models, and traditional ML models. You will also be involved in data engineering tasks such as cleaning, labeling, preprocessing, augmenting, and versioning datasets. Additionally, you will work on model deployment, MLOps, troubleshooting, optimization, collaboration with cross-functional teams, innovation, research, and documentation. To qualify for this role, you should have a Bachelor's degree in CS, AI, Data Science, or a related field, along with 1-2 years of experience in ML/AI roles. Proficiency in Python and ML frameworks like PyTorch, TensorFlow, Hugging Face, and scikit-learn is required. You should have a strong understanding of the AI project lifecycle and MLOps principles, as well as experience in data workflows, Docker, REST APIs, Git, and cloud platforms. Preferred skills for this role include experience with projects involving ChatGPT, LLaMA, Stable Diffusion, or similar models, familiarity with prompt engineering, RAG pipelines, vector DBs, exposure to CI/CD pipelines, ML metadata/versioning, a GitHub portfolio, or publications in generative AI, and awareness of ethics, bias mitigation, privacy, and compliance in AI. This is a full-time position located onsite. If you are a proactive individual with excellent analytical and problem-solving skills, strong communication abilities, and a passion for AI and ML, we encourage you to apply for this role and be a part of our AI/ML team.,

You are a talented and motivated AI Engineer specializing in Large Language Models (LLMs), Natural Language Processing (NLP), and Speech-to-Text technologies. As a valuable member of our dynamic team, your role involves developing, implementing, and optimizing cutting-edge AI solutions to enhance our products and services. Your primary focus will be on utilizing language models, constructing NLP systems, and integrating speech-to-text technologies to facilitate seamless communication and elevate user experiences. Your responsibilities include: - Fine-tuning and deploying large language models tailored for specific applications like chatbots, content generation, and customer support. - Evaluating and enhancing the performance of LLMs in real-world scenarios. - Designing and implementing NLP algorithms for tasks such as text classification, sentiment analysis, entity recognition, and summarization. - Working with extensive datasets to train and validate NLP models. - Collaborating with cross-functional teams to identify and resolve language-related challenges. - Developing and optimizing speech-to-text pipelines for various languages and dialects. - Integrating speech recognition systems with NLP and LLM solutions to achieve end-to-end functionality. - Staying updated on the latest advancements in automatic speech recognition (ASR). - Enhancing AI model efficiency for scalability and real-time processing. - Addressing biases, enhancing accuracy, and ensuring robustness in all models. - Keeping abreast of the latest research in LLM, NLP, and speech technologies. - Experimenting with emerging techniques and integrating them into company solutions. - Maintaining comprehensive documentation for models, processes, and systems. - Collaborating with product managers, software engineers, and other stakeholders. Requirements: - Minimum 8+ years of relevant experience. - Bachelor's/Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field. - Proven experience in LLM development using frameworks such as OpenAI, GPT, or similar. - Strong understanding of NLP techniques and libraries like spaCy, NLTK, Hugging Face. - Hands-on experience with speech-to-text systems such as Google Speech API, Whisper, or similar technologies. - Proficiency in programming languages like Python and frameworks like TensorFlow or PyTorch. - Strong problem-solving skills, collaborative mindset, and ability to manage multiple projects concurrently.,

We empower our people to stay resilient and relevant in a constantly changing world. We are looking for individuals who are always seeking creative ways to grow and learn, individuals who aspire to make a real impact, both now and in the future. If this resonates with you, then you would be a valuable addition to our dynamic international team. As a Graduate Trainee Engineer, you will have the opportunity to contribute significantly by: - Designing, developing, and optimizing NLP-driven AI solutions using cutting-edge models and techniques such as NER, embeddings, and summarization. - Building and operationalizing RAG pipelines and agentic workflows to facilitate intelligent, context-aware applications. - Fine-tuning, prompt-engineering, and deploying LLMs (such as OpenAI, Anthropic, Falcon, LLaMA, etc.) for specific domain use cases. - Collaborating with data scientists, backend developers, and cloud architects to construct scalable AI-first systems. - Evaluating and integrating third-party models/APIs and open-source libraries for generative use cases. - Continuously monitoring and enhancing model performance, latency, and accuracy in production environments. - Implementing observability, performance monitoring, and explainability features in deployed models. - Ensuring that solutions meet enterprise-level criteria for reliability, traceability, and maintainability. To excel in this role, you should possess: - A Master's or Bachelor's degree in Computer Science, Machine Learning, AI, or a related field. - Exposure to AI/ML, with expertise in NLP and Generative AI. - A solid understanding of LLM architectures, fine-tuning methods (such as LoRA, PEFT), embeddings, and vector search. - Previous experience in designing and deploying RAG pipelines and collaborating with multi-step agent architectures. - Proficiency in Python and frameworks like Lang Chain, Transformers (Hugging Face), Llama Index, Smol Agents, etc. - Familiarity with ML observability and explainability tools (e.g., Tru Era, Arize, Why Labs). - Knowledge of cloud-based ML services like AWS Sagemaker, AWS Bedrock, Azure OpenAI Service, Azure ML Studio, and Azure AI Foundry. - Hands-on experience in integrating LLM-based agents in production settings. - An understanding of real-time NLP challenges (streaming, latency optimization, multi-turn dialogues). - Familiarity with Lang Graph, function calling, and tools for orchestration in agent-based systems. - Exposure to infrastructure-as-code (Terraform/CDK) and DevOps for AI pipelines. - Domain knowledge in Electrification, Energy, or Industrial AI would be advantageous. Join us in Bangalore and be part of a team that is shaping the future of entire cities, countries, and beyond. At Siemens, we are a diverse community of over 312,000 minds working together to build a better tomorrow. We value equality and encourage applications from individuals who reflect the diversity of the communities we serve. Our employment decisions are based on qualifications, merit, and business requirements. Bring your curiosity and creativity to Siemens and be a part of shaping tomorrow with us. Explore more about Siemens careers at www.siemens.com/careers and discover the digital world of Siemens at www.siemens.com/careers/digitalminds.,

The role of Senior AI Professional at our organization requires a highly skilled individual who can work independently and lead AI projects from start to finish. You should have a broad experience with various AI tools, frameworks, and applications, and be comfortable in a fast-paced, innovation-driven setting. Your responsibilities will include designing, developing, and implementing AI solutions across different domains. You will manage AI projects independently, integrating tools such as NLP, Computer Vision, Generative AI, Predictive Analytics, Reinforcement Learning, and Recommendation Systems. Collaboration with cross-functional teams for data preparation, model development, testing, and deployment is essential. Staying updated with emerging AI technologies and optimizing models for performance, scalability, and cost efficiency are key aspects of the role. Additionally, documenting processes, models, and workflows for knowledge sharing within the team is crucial. To qualify for this position, you should hold a Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or a related field, along with at least 5 years of hands-on experience in AI/ML development. Proficiency in Python and major AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Hugging Face, OpenAI API, and LangChain is necessary. Experience in multiple AI domains including Natural Language Processing (NLP), Computer Vision, Generative AI (text, image, audio, video), Predictive Analytics & Forecasting, and Reinforcement Learning is required. You should possess strong skills in data preprocessing, feature engineering, model optimization, and familiarity with cloud AI platforms (AWS, Azure, GCP) and MLOps practices. Excellent problem-solving and communication abilities are essential for this role, along with the capacity to work independently with minimal supervision. Preference will be given to candidates based in Gurugram or Delhi, with prior experience in leading AI projects from scratch and exposure to AI integration in enterprise environments.,

As a Generative AI Lead, you will be responsible for spearheading the design, development, and implementation of cutting-edge GenAI solutions within enterprise-grade applications. Your role will encompass leveraging your expertise in Large Language Models (LLMs), prompt engineering, and scalable AI system architecture, coupled with hands-on experience in MLOps, cloud technologies, and data engineering. Your primary responsibilities will include designing and deploying scalable and secure GenAI solutions utilizing LLMs such as GPT, Claude, LLaMA, or Mistral. You will lead the architecture of Retrieval-Augmented Generation (RAG) pipelines using tools like LangChain, LlamaIndex, Weaviate, FAISS, or ElasticSearch. Additionally, you will be involved in prompt engineering, evaluation frameworks, and collaborating with cross-functional teams to integrate GenAI into existing workflows and applications. Moreover, you will develop reusable GenAI modules for various functions like summarization, Q&A bots, and document chat, while leveraging cloud-native platforms such as AWS Bedrock, Azure OpenAI, and Vertex AI for deployment and optimization. You will ensure robust monitoring and observability across GenAI deployments and apply MLOps practices for CI/CD, model versioning, validation, and research into emerging GenAI trends. To be successful in this role, you must possess at least 8 years of overall AI/ML experience, with a focus of at least 3 years on LLMs/GenAI. Strong programming skills in Python and proficiency in cloud platforms like AWS, Azure, and GCP are essential. You should also have experience in designing and deploying RAG pipelines, summarization engines, and chat-based applications, along with familiarity with MLOps tools and evaluation metrics for GenAI systems. Preferred qualifications include experience with fine-tuning open-source LLMs, knowledge of multi-modal AI, familiarity with domain-specific LLMs, and a track record of published work or contributions in the GenAI field. In summary, as a Generative AI Lead, you will play a pivotal role in driving innovation and excellence in the development and deployment of advanced GenAI solutions, making a significant impact on enterprise applications and workflows.,

As a Senior AI Professional, you will be responsible for designing, developing, and deploying AI solutions across various domains. Working independently, you will lead AI projects from concept to implementation, utilizing a diverse range of AI tools such as NLP, Computer Vision, Generative AI, Predictive Analytics, Reinforcement Learning, and Recommendation Systems. Collaboration with cross-functional teams for data preparation, model development, testing, and deployment will be a key aspect of your role. Furthermore, staying updated with emerging AI technologies and optimizing AI models for performance, scalability, and cost efficiency are essential responsibilities. Documentation of processes, models, and workflows for team knowledge sharing will also be part of your duties. You should hold a Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or a related field, along with at least 5 years of hands-on AI/ML development experience. Proficiency in Python and major AI/ML frameworks like TensorFlow, PyTorch, Scikit-learn, Hugging Face, OpenAI API, and LangChain is required. Experience in multiple AI domains including NLP, Computer Vision, Generative AI, Predictive Analytics & Forecasting, and Reinforcement Learning is essential. Strong skills in data preprocessing, feature engineering, and model optimization, along with familiarity with cloud AI platforms (AWS, Azure, GCP) and MLOps practices are necessary. Excellent problem-solving and communication skills, as well as the ability to work independently with minimal supervision, are crucial for success in this role. Candidates based in Gurugram or Delhi are preferred, with prior experience in leading AI projects from scratch and exposure to AI integration in enterprise environments being advantageous. If you are a highly skilled AI professional with a passion for innovation and the ability to work autonomously, this role offers a challenging opportunity to contribute to cutting-edge AI projects and drive technological advancements in a fast-paced environment.,

You should have at least 3+ years of relevant experience with the following skills: - Proficiency in Python, machine learning, deep learning, and NLP processing. - Experience in developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs. - Proficiency in Langchain, LLM. - Ability to prompt and optimize few-shot techniques to enhance LLM's performance on specific tasks. - Evaluate LLM's zero-shot and few-shot capabilities, fine-tuning hyperparameters, ensuring task generalization, and exploring model interpretability for robust web app integration. - Collaborate with ML and Integration engineers to leverage LLM's pre-trained potential, delivering contextually appropriate responses in a user-friendly web app. - Solid understanding of data structures, algorithms, and principles of software engineering. - Experience with vector databases RDBMS, MongoDB, and NoSQL databases. - Proficiency in working with embeddings. - Strong distributed systems skills and system architecture skills. - Experience in building and running a large platform at scale. - Hands-on experience with Python, Hugging Face, TensorFlow, Keras, PyTorch, Spark, or similar statistical tools. - Experience as a data modeling ML/NLP scientist, including performance tuning, fine-tuning, RLHF, and performance optimization. - Proficient with the integration of data from multiple sources and API design. - Good knowledge of Kubernetes and RESTful design. - Prior experience in developing public cloud services or open-source ML software is an advantage. You should also have a validated background with ML toolkits such as PyTorch, TensorFlow, Keras, Langchain, Llamadindex, SparkML, or Databricks. Your experience and strong knowledge of using AI/ML and particularly LLMs will be beneficial in this role.,

NVIDIA is seeking a dynamic and experienced Generative AI Solution Architect with deep expertise in training Large Language Models (LLMs) and building Retrieval-Augmented Generation (RAG) workflows. As a key member of our AI Solutions team, you'll drive innovation and impact in real-world deployments of cutting-edge generative AI technology. What You Will Be Doing Architect end-to-end generative AI solutions with a focus on LLMs and RAG workflows. Collaborate with customers to understand business problems and translate them into tailored LLM-based solutions. Design and lead workshops and technical sessions to define, optimize, and deploy RAG-based and LLM-powered systems. Train and fine-tune state-of-the-art LLMs on NVIDIA platforms, optimizing for performance, cost, and efficiency. Deploy and integrate LLMs and RAG workflows in cloud and on-premise environments, enabling real-world applications. Work closely with NVIDIA engineering and product teams, influencing the evolution of generative AI tools and technologies. Build and share best practices for model training, deployment, and performance optimization using NVIDIA GPUs and AI platforms. What We Need To See Master's or Ph.D. in Computer Science, AI, or a related field 5+ years of hands-on experience with LLM training, deployment, and production optimization Deep understanding of language models like GPT-3, BERT, and experience with RAG Proficient in PyTorch, TensorFlow, and Hugging Face Transformers Familiar with GPU acceleration, distributed computing, and inference tuning on NVIDIA hardware Experience presenting to clients and leading cross-functional collaboration Strong communication skillsable to clearly explain technical details to diverse audiences Ways To Stand Out From The Crowd Experience deploying LLMs in cloud (AWS, Azure, GCP) and on-prem clusters Proficiency with Docker, Kubernetes, and GPU cluster management Proven ability to optimize LLM inference for speed, memory, and cost Hands-on experience with NVIDIA GPU technologies, profiling, and distributed model execution If you're passionate about the future of AI and want to help define how organizations use LLMs at scale, we want to hear from you. NVIDIA is widely considered one of the most desirable employers in techjoin us in shaping what's next. We are an equal opportunity employer and committed to diversity in our workforce.

NVIDIA is seeking a dynamic and experienced Generative AI Solution Architect with deep expertise in training Large Language Models (LLMs) and building Retrieval-Augmented Generation (RAG) workflows. As a key member of our AI Solutions team, you'll drive innovation and impact in real-world deployments of cutting-edge generative AI technology. What You Will Be Doing Architect end-to-end generative AI solutions with a focus on LLMs and RAG workflows. Collaborate with customers to understand business problems and translate them into tailored LLM-based solutions. Design and lead workshops and technical sessions to define, optimize, and deploy RAG-based and LLM-powered systems. Train and fine-tune state-of-the-art LLMs on NVIDIA platforms, optimizing for performance, cost, and efficiency. Deploy and integrate LLMs and RAG workflows in cloud and on-premise environments, enabling real-world applications. Work closely with NVIDIA engineering and product teams, influencing the evolution of generative AI tools and technologies. Build and share best practices for model training, deployment, and performance optimization using NVIDIA GPUs and AI platforms. What We Need To See Master's or Ph.D. in Computer Science, AI, or a related field 5+ years of hands-on experience with LLM training, deployment, and production optimization Deep understanding of language models like GPT-3, BERT, and experience with RAG Proficient in PyTorch, TensorFlow, and Hugging Face Transformers Familiar with GPU acceleration, distributed computing, and inference tuning on NVIDIA hardware Experience presenting to clients and leading cross-functional collaboration Strong communication skillsable to clearly explain technical details to diverse audiences Ways To Stand Out From The Crowd Experience deploying LLMs in cloud (AWS, Azure, GCP) and on-prem clusters Proficiency with Docker, Kubernetes, and GPU cluster management Proven ability to optimize LLM inference for speed, memory, and cost Hands-on experience with NVIDIA GPU technologies, profiling, and distributed model execution If you're passionate about the future of AI and want to help define how organizations use LLMs at scale, we want to hear from you. NVIDIA is widely considered one of the most desirable employers in techjoin us in shaping what's next. We are an equal opportunity employer and committed to diversity in our workforce.

You should have a minimum of 5 years of experience in AI/ML with at least 2+ years in NLP, LLMs, and Generative AI. Your expertise should include ML architecture design, end-to-end model development, and deployment in production systems. Proficiency in Python is essential, along with deep experience in ML libraries and frameworks like TensorFlow, PyTorch, Hugging Face, and LangChain. A sound knowledge of transformer models, embeddings, tokenization, and vector databases such as FAISS and Pinecone is required. Experience with cloud-native AI solutions on AWS, Azure, or GCP is preferred. Familiarity with MLOps, model versioning, containerization using Docker, and orchestration tools like Kubeflow and MLflow is a plus. Your responsibilities will include architecting and implementing end-to-end machine learning and Generative AI solutions for real-world applications. You will design, fine-tune, and deploy models using transformers, embeddings, tokenization, and LLMs for tasks like summarization, classification, question answering, and content generation. Developing and maintaining high-quality, production-grade ML code in Python using libraries such as TensorFlow, PyTorch, Hugging Face, and LangChain is crucial. Furthermore, you will be responsible for building and optimizing retrieval-augmented generation (RAG) pipelines by integrating LLMs with structured and unstructured data. Working with vector databases like FAISS and Pinecone to manage semantic search and context retrieval efficiently will be part of your role. Utilizing cloud-native AI services for model training, deployment, and scaling on platforms like AWS, GCP, and Azure is expected. Implementing MLOps best practices, including model versioning, containerization using Docker, orchestration with tools like Kubeflow and MLflow, and following CI/CD procedures are also key responsibilities. Strong problem-solving skills, architectural thinking, and the ability to lead complex AI initiatives, along with excellent communication, stakeholder management, and technical leadership capabilities, are essential for this role.,

We are seeking a skilled and passionate Prompt Engineer with expertise in Prompt Engineering and LLM-based application development. As a Prompt Engineer, you will be responsible for designing, developing, and scaling GenAI-powered applications using cutting-edge technologies in AI, full-stack development, and cloud computing. Your key responsibilities will include designing and developing AI applications utilizing Large Language Models (LLMs) such as GPT-4, Claude, or LLaMA. You will be tasked with writing, optimizing, and evaluating prompts for various tasks and use cases. Proficiency in Python, JavaScript (React/Node.js), or other full-stack technologies is essential for this role. Additionally, you will be expected to build responsive frontend interfaces using frameworks like React.js, Vue.js, or similar. Integration with AI APIs such as OpenAI, Azure OpenAI, Cohere, etc., and working with frameworks like LangChain, LlamaIndex, and RAG pipelines will be part of your daily tasks. Implementing vector databases like Pinecone, Weaviate, and FAISS for knowledge retrieval is also crucial. Collaboration with cross-functional teams for system integration and deployment to ensure best practices in coding, testing, DevOps, and cloud deployment is a key aspect of this role. The ideal candidate should possess proficiency in Python, JavaScript (React/Node.js), or other full-stack technologies and have experience with AI/ML frameworks like TensorFlow, PyTorch, and Hugging Face. Hands-on experience with Prompt Engineering for Large Language Models (LLMs) such as GPT, Claude, LLaMA, etc., and knowledge of RAG, LangChain, or LlamaIndex are highly desired. Familiarity with AI APIs like OpenAI, Azure OpenAI, and backend development using FastAPI, Flask, or Express is required. Experience in frontend development using React or Vue.js, familiarity with CI/CD, Docker, and cloud platforms (AWS, Azure, GCP) are essential skills for this role. Preferred skills include experience with LangChain, LlamaIndex, or similar frameworks, familiarity with tools like Hugging Face, OpenAI Playground, Azure OpenAI Studio, knowledge of MLOps tools, and data pipelines, and understanding of prompt tuning and fine-tuning LLMs.,

As a Senior AI Engineer specialized in Computer Vision and Large Language Models (LLMs), your main responsibility will be to design, develop, and implement advanced AI/ML solutions to address real-world challenges. You will be expected to possess a Master's degree in Artificial Intelligence, Machine Learning, Computer Science, or a related field, along with a strong understanding of Fast API and Kubernetes. Your technical expertise should include a deep knowledge of various AI/ML algorithms (supervised, unsupervised, reinforcement learning, deep learning) and proficiency in utilizing AI tools and frameworks such as TensorFlow, PyTorch, Hugging Face, OpenAI, LangChain, among others. Expertise in Computer Vision tasks like object detection, image segmentation, tracking, and OCR, as well as experience with Large Language Models (LLMs) including fine-tuning, prompt engineering, and API integrations, will be essential for this role. You should be capable of independently designing and developing end-to-end AI products from concept to deployment and orchestration, with a good understanding of Azure and AWS. Strong problem-solving skills, analytical thinking, and effective communication and documentation abilities are crucial for success in this position. Your responsibilities will involve building production-ready computer vision and LLM-based applications, researching and integrating the latest AI tools and algorithms into product development, collaborating with cross-functional teams to deliver AI-powered solutions, and optimizing models for performance, scalability, and accuracy. This full-time role based in Gurugram / Delhi NCR requires candidates who prefer working in an in-person setting. In return, you will have the opportunity to work on cutting-edge AI projects, lead product development initiatives, and be part of a collaborative and innovation-driven work culture.,

You are a driven and innovative AI Engineer with hands-on experience in Generative AI (GenAI) and LLM-based solutions. This is an exciting opportunity to work on cutting-edge projects that push the boundaries of automation, intelligent agents, and natural language understanding. As part of our growing AI team, you'll collaborate closely with product managers, data scientists, and full-stack developers to design, build, and deploy scalable AI systems. Your responsibilities will include building and fine-tuning intelligent agents and chatbots using LLMs, designing and developing tools to process and analyze unstructured data (text, PDFs, images), implementing Retrieval-Augmented Generation (RAG) pipelines, collaborating with cross-functional teams to integrate GenAI-based solutions, contributing to architectural decisions for scalable AI systems, and staying updated on the latest advancements in LLMs, GenAI, and AI tooling. Key Skills & Tools: - Languages & Frameworks: Python (core), FastAPI (preferred), LangChain - AI/ML Tools: LangChain, OpenAI APIs, Hugging Face, Transformers, Vector DBs such as FAISS and ChromaDB, LLM Orchestration & Deployment - Project Experience: GenAI projects using unstructured data, LLM-powered tools or agents, Retrieval-Augmented Generation (RAG) - DevOps/Tooling: Git, Docker, Postman, CI/CD - Databases: MongoDB, PostgreSQL, ChromaDB (for embeddings/metadata) - Cloud Platforms (Preferred): AWS, GCP, or Azure (especially for AI integrations) - Soft Skills: Passion for AI and innovation, Curiosity and adaptability to emerging tech, Strong problem-solving and analytical mindset, Excellent communication and teamwork skills As part of the team, you will have hands-on exposure to LLM and GenAI technologies, performance-based incentives, continuous learning & upskilling opportunities, flexible and transparent work arrangements, and fun & team engagement activities. This is a full-time, permanent position with an application deadline of 09/08/2025.,

As an intern at IntelliSQr, you will be responsible for assisting in various tasks related to data processing and machine learning projects. Your day-to-day responsibilities will include: - Assisting in the collection, cleaning, and preprocessing of data for Machine Learning (ML), Deep Learning (DL), and GenAI projects. - Supporting the development, training, and evaluation of machine learning and deep learning models. - Working on fine-tuning and evaluating Large Language Models (LLMs) for specific tasks. - Exploring and experimenting with GenAI frameworks and tools such as LangChain, LlamaIndex, Hugging Face, Transformers. - Contributing to the building and testing of AI/ML/DL pipelines and GenAI-powered applications. - Conducting literature reviews to stay updated on recent advancements in ML, DL, and LLMs. - Performing prompt engineering and optimizing LLM outputs for relevance and accuracy. - Documenting model architectures, experiments, findings, and improvement suggestions. - Collaborating with AI engineers and product teams to integrate models into real-world applications. - Participating in code reviews, version control, and team discussions to enhance learning and contribution. About Company: IntelliSQr is a technology procurement platform specializing in business analytics solutions across various industries. The company aims to simplify the process for customers by recommending suitable solutions based on their business and technical requirements.,

We are looking for an experienced AI Engineer to join our team and lead the development of cutting-edge AI solutions, particularly focusing on Generative AI and its applications in the legal domain. The ideal candidate should have a solid background in constructing and training AI/ML models from the ground up, deploying them in production environments, and working with advanced technologies such as NLP, LLMs, and vector databases. If you have experience in creating AI models, especially custom Large Language Models (LLMs) or domain-specific models, you are well-suited for this role. Your responsibilities will include designing, developing, and training custom AI models, particularly Generative AI and NLP-based models tailored for legal applications. You will also be tasked with implementing techniques to fine-tune and optimize large language models for domain-specific use cases, building models from scratch as necessary while ensuring scalability, accuracy, and efficiency. Additionally, you will design and implement AI-driven systems using Python and frameworks like FastAPI and Django for robust API development, as well as develop and integrate vector databases for semantic search, embeddings, and retrieval-augmented generation (RAG). Furthermore, you will manage data pipelines, including preprocessing and cleansing unstructured text such as legal documents, contracts, and case law. Working with SQL and PostgreSQL databases for structured data storage and retrieval will also be a part of your role. You will develop generative solutions for tasks like document summarization, legal drafting, knowledge extraction, and automated reasoning, leveraging modern transformer architectures such as GPT, BERT, LLaMA, Falcon, among others, to build advanced capabilities. Collaboration with product, legal, and engineering teams to comprehend requirements and deliver solutions in an Agile environment using tools like Jira and GitHub is essential. Mentoring junior engineers and contributing to knowledge sharing within the team are also key responsibilities. Staying updated with the latest advancements in AI, LLMs, RAG, and Generative AI technologies and applying them to real-world scenarios, as well as proposing innovative solutions to enhance the efficiency, accuracy, and scalability of existing systems are also expected from you. Preferred qualifications for this role include a Bachelors or Masters in Computer Science, AI/ML, Data Science, or related fields, strong expertise in Python programming, familiarity with frameworks like FastAPI and Django, experience with TensorFlow, PyTorch, Hugging Face, and preferred knowledge of LangChain. Additionally, experience with databases like MySQL, PostgreSQL, and exposure to Vector Stores (e.g., Pinecone, Weaviate, FAISS), as well as familiarity with containerization (Docker), CI/CD pipelines, and tools like GitHub, Jira, and Agile methodology are preferred. Candidates with 8+ years of experience in AI/ML engineering, a proven track record of building and deploying custom AI models into production, hands-on experience with Generative AI, LLM fine-tuning, and retrieval-augmented generation (RAG) are highly encouraged to apply. Experience with cloud platforms (AWS, Azure, GCP) for AI deployments, knowledge of MLOps practices for model lifecycle management, contributions to open-source AI/ML projects, and prior experience in developing legal-specific AI tools or solutions are considered advantageous for this role.,

You are a talented and innovative AI/ML Engineer with a strong background in machine learning and deep learning. You have a keen interest in Generative AI (GenAI) and are excited to explore, implement, and scale GenAI models. Your primary responsibilities include designing and deploying end-to-end AI/ML solutions, experimenting with cutting-edge GenAI frameworks and tools, and collaborating with cross-functional teams to solve business problems using ML solutions. Your key responsibilities involve designing and developing robust ML models, including traditional and deep learning approaches. You will also build, train, fine-tune, and deploy Generative AI models for various use cases such as text, image, or code generation. Utilizing AWS services like SageMaker, Lambda, EC2, S3, and Glue to build scalable AI/ML solutions is an essential part of your role. Additionally, you will create and automate ML pipelines using CI/CD and MLOps best practices, conduct data preprocessing, feature engineering, and EDA for model development, and ensure model performance, fairness, and explainability throughout the lifecycle. To excel in this role, you should hold a Bachelor's/Masters degree in Computer Science, AI/ML, Data Science, or a related field and have at least 3 years of hands-on experience in machine learning and deep learning using Python with TensorFlow, PyTorch, Hugging Face, etc. Strong hands-on experience with AWS AI/ML services, experience in deploying LLMs or transformer-based models in production, and familiarity with GenAI tools like Hugging Face Transformers, LangChain, OpenAI API, Bedrock, or LLamaIndex are required. You should also possess working knowledge of REST APIs, microservices, and containerized deployments, proficiency in MLOps tools such as MLflow, SageMaker Pipelines, or Kubeflow, and strong communication skills to present complex ML concepts clearly. Preferred qualifications include experience with prompt engineering, fine-tuning, or RAG techniques, AWS Machine Learning Specialty certification or equivalent, exposure to NLP, computer vision, or multi-modal GenAI models, and contributions to open-source GenAI projects or research. Stay updated with the latest trends in GenAI and propose innovative solutions using LLMs or transformer-based architectures to drive continuous improvement in AI/ML solutions.,

As a Data Scientist specializing in GenAI within the Banking domain, you will utilize your extensive experience of over 10 years in Data Science, with a focus of 3+ years specifically in GenAI. Your expertise will be instrumental in developing, training, and fine-tuning GenAI models such as LLMs and GPT for various banking use cases. You will collaborate closely with business and product teams to design and implement predictive models, NLP solutions, and recommendation systems tailored to the financial industry. A key aspect of your role will involve working with large volumes of both structured and unstructured financial data to derive valuable insights. Moreover, you will be responsible for ensuring the ethical and compliant use of AI by incorporating practices related to fairness, explainability, and compliance into the model outputs. Deployment of these models using MLOps practices like CI/CD pipelines and model monitoring will also be within your purview. Your skill set must include a strong proficiency in Python programming, along with a deep understanding of libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch. Hands-on experience with GenAI tools like OpenAI, Hugging Face, LangChain, and Azure OpenAI will be crucial for success in this role. Furthermore, your expertise in NLP, prompt engineering, embeddings, and vector databases will play a pivotal role in building models for critical banking functions like credit risk assessment, fraud detection, and customer segmentation. While not mandatory, it would be advantageous to possess knowledge of LLM fine-tuning and retrieval-augmented generation (RAG) in addition to familiarity with data privacy and compliance regulations such as GDPR and RBI guidelines as they pertain to AI systems. Your understanding of banking data, processes, and regulatory requirements will be key in delivering effective AI-driven solutions within the financial services industry.,

As an AI Lead with over 4 years of experience, your primary responsibility will be to lead the design, development, and deployment of advanced AI solutions focusing on Natural Language Processing (NLP), Large Language Models (LLM) fine-tuning, and implementing machine learning models to solve real-world challenges. You will collaborate with product, engineering, and domain experts to transform innovative ideas into intelligent solutions. Your key responsibilities will include guiding junior engineers, building and optimizing Large Language Models (LLMs) and NLP pipelines, creating machine learning workflows for various systems, integrating AI models into production environments ensuring scalability and performance, conducting data preprocessing, feature engineering, and experimentation, aligning AI outputs with business objectives by collaborating with cross-functional teams, and staying abreast of the latest advancements in deep learning, LLMs, and generative AI. To excel in this role, you should possess 4+ years of hands-on experience in AI/ML engineering, proficiency in Python along with expertise in TensorFlow, PyTorch, or Hugging Face, a strong background in Natural Language Processing (NLP), prior experience with Large Language Models (LLMs) such as GPT, BERT, LLaMA, and transformer architectures, familiarity with ML Ops tools, version control, and deployment practices, a solid understanding of AI ethics, model evaluation, and optimization, excellent communication skills, and the ability to mentor and guide junior engineers. A Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field would be an added advantage.,

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world's most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities where you can make a difference and no two days are the same. Your role as a Junior Machine Learning Developer at Capgemini Engineering involves being part of a dynamic team working on cutting-edge AI and machine learning solutions. This role offers an exciting opportunity for a motivated individual to learn and grow their skills in a fast-paced, collaborative environment. You will assist senior developers in developing, testing, and deploying AI models while gaining hands-on experience with machine learning frameworks and real-world AI applications. The ideal candidate should have a basic understanding of machine learning frameworks such as TensorFlow, PyTorch, or Hugging Face, knowledge of neural network architectures, particularly in areas like Transformers and basic deep learning models, familiarity with Python programming and essential ML libraries (NumPy, Pandas, Scikit-learn), exposure to NLP (Natural Language Processing) concepts and basic text processing tasks, some experience with cloud platforms (AWS, GCP, or Azure) for deploying simple AI models, and understanding of basic databases and their integration with AI systems (NoSQL or SQL databases). Your profile should include a strong eagerness to learn and adapt to new technologies in the AI and machine learning field, ability to work under guidance and collaborate within a team environment, good problem-solving abilities and analytical thinking, effective communication skills to discuss technical issues and progress with the team, a Bachelor's degree in computer science, Data Science, Artificial Intelligence, or related fields, and 2-4 years of experience in machine learning, AI, or related areas (internships or academic projects are a plus). Preferred Skills (Nice-to-Have) include exposure to basic machine learning deployment tools or practices, familiarity with any vector databases (ChromaDB, Pinecone, Weaviate, Milvus, FAISS) or graph databases (Neo4j, TigerGraph), interest in generative AI or graph-based AI solutions, involvement in open-source projects or personal contributions to machine learning communities, and understanding of ethical AI principles or data privacy basics. At Capgemini, you can work on cutting-edge projects in tech and engineering with industry leaders or create solutions to overcome societal and environmental challenges. Every Monday, kick off the week with a musical performance by our in-house band - The Rubber Band. Additionally, get to participate in internal sports events, yoga challenges, or marathons. Capgemini is committed to ensuring that people of all backgrounds feel encouraged and have a sense of belonging. You are valued for who you are, and you can bring your original self to work. Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, creating tangible impact for enterprises and society. With over 55 years of heritage, Capgemini is trusted by its clients to unlock the value of technology and address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market-leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.,