21 Huggingface Transformers Jobs

As a GenAI Developer, you will be responsible for the end-to-end development of GenAI applications. This includes designing and building applications using LLMs such as LLaMA, Mistral, GPT-J, Falcon, and Claude. You will also implement RAG pipelines using vector databases like FAISS, ChromaDB, or Weaviate, and create and tune prompt templates, guardrails, and output parsers using tools like LangChain, Haystack, or LlamaIndex. In the realm of Agentic AI & Autonomy, you will be tasked with developing AI agents that leverage planning, memory, tools, and self-reflection. This may involve utilizing tools such as AutoGen, CrewAI, or LangGraph to build task-oriented chains with autonomous behaviors for decision-making and workflow automation. Your role will also encompass Model Training & Fine-Tuning, where you will perform SFT on open-source models using libraries like HuggingFace Transformers, PEFT, LoRA, or QLoRA. Additionally, you will evaluate model performance using GenAI metrics and frameworks such as DeepEval and TruLens. ML System Integration will be a key aspect of your responsibilities, involving the use of ML libraries like Scikit-learn, TensorFlow, PyTorch, and XGBoost to integrate traditional ML pipelines alongside GenAI components. You will be expected to develop APIs and microservices using FastAPI or Flask to expose GenAI/ML services. Furthermore, you will contribute to ensuring the security, observability, and control of AI workflows by employing red-teaming, logging, tracing, and policy controls. Additionally, you will play a role in developing tools and dashboards to explain and evaluate model behavior. The core requirements for this role include proficiency in Python, with strong coding skills and the ability to write modular, production-grade code. You should have experience in Generative AI, including using and fine-tuning LLMs, working on RAG, SFT, and prompt engineering, and being familiar with open-source LLMs and frameworks like HuggingFace and LangChain. Exposure to building multi-agent workflows using tools such as AutoGen, CrewAI, or LangGraph is also desired. In terms of ML Foundation, you should have a practical understanding of supervised/unsupervised ML models and experience using Scikit-learn, XGBoost, PyTorch, and TensorFlow. Preferred (Bonus) Skills include experience with Vector DBs like FAISS, Pinecone, ChromaDB, model evaluation tools such as DeepEval and TruLens, LLMOps tools like Weights & Biases, MLflow, BentoML, cloud services like AWS (SageMaker, Bedrock), GCP, or Azure, as well as familiarity with Docker, Git, and CI/CD for deployment.,

You will be responsible for developing, fine-tuning, and evaluating vision-language models such as CLIP, Flamingo, BLIP, GPT-4V, LLaVA, among others. Your role will involve designing and constructing multimodal pipelines that fuse image/video inputs with natural language comprehension or generation. Working with extensive image-text datasets like LAION, COCO, Visual Genome for training and validation will be a key part of your job. You will also be implementing zero-shot/few-shot multimodal inference, retrieval, captioning, VQA (Visual Question Answering), grounding, etc. It is essential to collaborate closely with product teams, ML engineers, and data scientists to deliver practical multimodal applications. Additionally, optimizing model inference performance and resource utilization in production environments using ONNX, TensorRT, etc., will be expected. Conducting error analysis, ablation studies, and suggesting enhancements in visual-language alignment, as well as contributing to research papers, documentation, or patents if in a research-oriented team, are also part of the responsibilities. To excel in this role, you should hold a Bachelors/Masters/PhD in Computer Science, AI, Machine Learning, or a related field. You must possess at least 2+ years of experience in computer vision or NLP, with a minimum of 1+ year specifically in multimodal ML or VLMs. Strong proficiency in Python programming, along with hands-on experience in libraries like PyTorch, HuggingFace Transformers, OpenCV, torchvision, is required. Familiarity with VLM architectures such as CLIP, BLIP, Flamingo, LLaVA, Kosmos, GPT-4V, etc., is expected. You should also have prior experience in dataset curation, image-caption pair processing, and image-text embedding strategies. A solid grasp of transformers, cross-attention mechanisms, and contrastive learning will be advantageous for this role. This is a full-time position with a day shift schedule. The work location is in-person.,

You are a skilled and innovative AI Developer with hands-on experience in OpenAI APIs, HuggingFace Transformers, and prompt engineering. Your main responsibility will be to design, develop, and deploy intelligent systems for text, image, and code generation by utilizing modern AI technologies and large language models (LLMs). In this role, you will play a crucial part in constructing conversational agents, generative pipelines, and integrating AI into real-world web applications. You will be tasked with utilizing OpenAI APIs such as ChatGPT and DALLE for advanced natural language and image generation tasks. Additionally, you will implement and fine-tune pre-trained models using HuggingFace Transformers. Your role will involve designing optimal prompts for LLMs to enhance model output accuracy and relevance. You are expected to develop and integrate embedding-based search systems employing OpenAI Embeddings, FAISS, or Pinecone. Moreover, you will be responsible for building scalable content generation pipelines for text, image, and code automation. Your tasks will also include fine-tuning of LLMs using LoRA, PEFT, and HuggingFace Trainer APIs, applying NLP techniques with tools like spaCy, NLTK, and Transformers, and developing intelligent chatbots using platforms like Rasa, Dialogflow, or Microsoft Bot Framework. You will integrate AI solutions into web applications using React.js and manage user session and context flow to provide personalized and coherent conversational experiences. Additionally, you will handle data preprocessing using Pandas, regex, and custom scripts, and utilize scikit-learn, XGBoost, and LightGBM for classical ML tasks when necessary. For this role, you are required to hold a Bachelors or Masters degree in Computer Science, AI, Data Science, or a related field. You should have proven experience with OpenAI GPT-based models and image generation APIs, expertise in Prompt Engineering and model behavior optimization, as well as solid experience with embedding-based search and vector databases. Strong command over React.js and JavaScript for frontend-AI integration, a good understanding of ML frameworks and model deployment workflows, and excellent communication and problem-solving skills are essential. Preferred qualifications include experience deploying AI models in production environments, familiarity with LangChain or similar LLM orchestration tools, and previous work on projects involving Generative AI, conversational AI, or custom LLM training.,

As a crucial member of the team, you will play a pivotal role in various machine learning initiatives, contributing to the development of conversational AI bots, RAG system, and traditional ML problem-solving for the observability platform. Your responsibilities will involve both operational and engineering tasks such as building production-ready inference pipelines, deploying and versioning models, and implementing continuous validation processes. Within the LLM domain, you will be tasked with fine-tuning generative AI models, designing agentic language chains, and prototyping recommender system experiments. This role offers you the opportunity to significantly impact AI-driven solutions in diverse domains, pushing the boundaries of machine learning and embracing diverse challenges along the way. To excel in this position, you should demonstrate proficiency in software engineering design practices, experience with transformer models and text embeddings, a track record of deploying and managing ML models in production environments, and familiarity with common ML/NLP libraries like PyTorch, Tensorflow, HuggingFace Transformers, and SpaCy. You should have over 5 years of experience developing production-grade applications in Python, proficiency in Kubernetes and containers, and familiarity with concepts/libraries such as sklearn, kubeflow, argo, and seldon. Expertise in Python, C++, Kotlin, or similar programming languages, along with experience in designing, developing, and testing scalable distributed systems, is essential. Moreover, knowledge of message broker systems (e.g., Kafka, RabbitMQ), application instrumentation and monitoring practices, ML workflow management tools like AirFlow and Sagemaker, and fine-tuning generative AI models for enhanced performance will be valuable. Designing AI Agents for conversational AI applications, experimenting with new techniques for observability use cases, building and maintaining inference pipelines, managing deployment and model versioning pipelines, and developing tooling for continuous model validation in production environments are key aspects of this role. Bonus points will be awarded if you have familiarity with the AWS ecosystem or past experience working on projects involving the construction of agentic language chains. Please note that visa sponsorship is not available for this position. At our company, fostering a diverse, welcoming, and inclusive environment is a priority. We encourage individuals from different backgrounds and abilities to bring their authentic selves to work, celebrating the diverse paths that brought them to us. Our mission is to create the best products and company possible, inspired by the unique experiences and perspectives of our team members. We value candidates who connect with our mission and values beyond just meeting requirements. If you need a reasonable accommodation during the application or recruiting process, please contact resume@newrelic.com. We believe in empowering all team members to achieve success through a flexible workforce model that supports various work environments, including fully office-based, fully remote, or hybrid setups. As part of our hiring process, all hires must verify identity and eligibility to work, including completing employment eligibility verification. A criminal background check is required due to our responsibility for safeguarding customer data. Qualified applicants with arrest and conviction records will be considered based on individual circumstances and applicable laws. For more information, review our Applicant Privacy Notice at https://newrelic.com/termsandconditions/applicant-privacy-policy.,

Prismforce is a Vertical SaaS company at the forefront of revolutionizing the Talent Supply Chain for global Technology, R&D/Engineering, and IT Services companies. Through our AI-powered product suite, we aim to enhance business performance by facilitating operational flexibility, accelerating decision-making processes, and boosting profitability. Our ultimate mission is to establish ourselves as the premier industry cloud/SaaS platform for tech services and talent organizations worldwide. We are currently seeking a highly experienced Data Scientist to join our team in Bangalore within the AI & ML department. In this role, you will be instrumental in leveraging your expertise in Natural Language Processing (NLP) and machine learning to develop customized AI solutions that address real-world talent intelligence challenges. The scope of your responsibilities will encompass a wide range of tasks, from data exploration and model development to evaluation and deployment, all while emphasizing the creation of robust, scalable systems utilizing cutting-edge techniques. As a Data Scientist at Prismforce, your key responsibilities will include: - Developing and fine-tuning models for Named Entity Recognition (NER), text classification, semantic similarity, and clustering - Utilizing pretrained embeddings, transformers, and Large Language Models (LLMs) to extract and standardize structured data from unstructured text - Designing and conducting experiments to assess model performance and drive enhancements - Collaborating closely with product and engineering teams to translate models into reliable, production-ready solutions - Continuously researching and exploring open-source tools to enhance performance and scalability The ideal candidate for this position should possess the following qualifications: - A minimum of 13 years of hands-on experience in applied NLP and ML - Proficiency in Python programming, along with familiarity with Pandas, Scikit-learn, PyTorch, or TensorFlow - Knowledge of modern NLP toolkits such as Spacy, HuggingFace Transformers, SBERT, among others - A solid grasp of embedding models, attention mechanisms, and evaluation metrics - The ability to deconstruct abstract problems and develop tailored, data-driven solutions Additionally, the following skills and experiences would be considered advantageous: - Prior exposure to LLM APIs, prompt engineering, or metadata generation using LLMs - Familiarity with knowledge graphs, taxonomy design, or vector databases - Contributions to open-source NLP tools or involvement in research projects within the field If you are a seasoned Data Scientist with a passion for NLP and ML, and you are eager to make a significant impact within our innovative team, we encourage you to apply and become a part of Prismforce's mission to reshape the future of talent intelligence.,

As a Research Engineer-II at Attentive.ai, you will play a crucial role in the AI research team dedicated to revolutionizing the construction sector with state-of-the-art deep learning, computer vision, and NLP technologies. Your main responsibility will involve developing intelligent systems for automated construction take-off and estimation by handling unstructured data such as blueprints, drawings (including SVGs), and PDF documents. Your tasks will encompass various aspects such as contributing to research and development projects focused on Computer Vision, Image Processing, and Deep Learning applied to construction-related data. You will be involved in building and enhancing models to extract valuable insights from documents like blueprints, scanned PDFs, and SVG files. Additionally, you will participate in developing multi-modal models that merge vision with language-based features (NLP/LLMs), following the best practices of data science and machine learning. Collaboration with cross-functional teams, including software engineers, ML researchers, and product teams, will be a key part of your role as you work towards translating research concepts into practical applications. Writing clean, scalable, and production-ready code using Python and frameworks like PyTorch, TensorFlow, or HuggingFace will be essential to your success in this position. Moreover, keeping abreast of the latest advancements in computer vision and machine learning and assessing their relevance to the challenges in the construction industry will be crucial. To excel in this role, you should possess at least 3-5 years of experience in applied AI/ML research with a strong emphasis on Computer Vision and Deep Learning. A solid grasp of image processing, visual document understanding, and feature extraction from visual data is necessary. Knowledge of SVG graphics, NLP, or LLM-based architectures would be advantageous. Proficiency in Python and ML frameworks such as PyTorch, OpenCV, TensorFlow, and HuggingFace is essential. Hands-on experience with model optimization techniques, version control systems, project tracking tools, and cloud environments is desirable. If you are passionate about building innovative solutions, possess strong analytical and problem-solving skills, and thrive in a fast-paced, agile environment, this role offers you the opportunity to be part of a groundbreaking team at Attentive.ai. You will have the chance to work on a cutting-edge AI solution for the construction industry, gain exposure to real-world AI deployment, and engage in cutting-edge research in vision and multimodal learning. The culture at Attentive.ai fosters ownership, innovation, and growth, providing avenues for rapid learning, mentorship, and career advancement.,

As an AI Developer at RMgX, a Gurgaon based digital product innovation & consulting firm, you will be responsible for designing, developing, and deploying AI solutions using Large Language Models (LLMs) such as GPT, LLaMA, Claude, or Mistral. You will fine-tune and customize pre-trained LLMs for business-specific use cases and build NLP pipelines for classification, summarization, semantic search, etc. Additionally, you will collaborate with cross-functional teams to integrate LLM-based features into applications and analyze and improve model performance using appropriate metrics. To excel in this role, you should have at least 12 years of experience in AI/ML development with a specific focus on NLP and LLM-based solutions. You must possess strong hands-on experience in Python and AI/ML libraries like HuggingFace Transformers, LangChain, PyTorch, TensorFlow, etc. Proficiency in working with closed-source models via APIs (e.g., OpenAI, Gemini) is essential, along with an understanding of prompt engineering, embeddings, and vector databases like FAISS, Milvus, or Pinecone. Experience in deploying models using REST APIs, Docker, and cloud platforms such as AWS/GCP/Azure is required. Familiarity with MLOps and version control tools like Git, MLflow, etc., and knowledge of LLMOps platforms such as LangSmith, Weights & Biases will be advantageous. Strong problem-solving skills, attention to detail, and the ability to work in an agile environment are key attributes for this role. A Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field is preferred. In return, RMgX offers flexible working hours, fixed weekends off, health insurance, personal accident insurance, BYOD (Bring Your Own Device) Benefit, and a Laptop Buyback Scheme. Join RMgX to be a part of a team that values quality, innovation, and the continuous pursuit of excellence in AI development.,

At Quark, we have been at the forefront of revolutionizing graphic design, digital publishing, and content automation since 1981. With over four decades of experience, we empower organizations to master their content lifecycle through cutting-edge design, automation, and intelligence. Our innovative software solutions allow customers to efficiently create, manage, publish, and analyze their content. As we enter a new phase of growth, we are seeking exceptional individuals to join our global team. Quark serves as the foundation for all content, just like a Quark forms the basis of all matter in science. Our commitment to excellence is encapsulated in our tagline, "brilliant content that works." With a diverse global workforce of approximately 250 professionals, we foster an inclusive culture that values and celebrates our team's diversity. As a highly motivated Senior AI Engineer at Quark Inc., you will play a crucial role in our expanding AI team. Your primary responsibilities will include building scalable AI systems that focus on document conversion, domain-adaptive model training, and conversational AI. The ideal candidate will possess a strong background in Natural Language Processing (NLP), experience with both open-source and commercial AI platforms, and a proven track record of delivering AI solutions in production environments. Your key responsibilities will include: - Designing and implementing AI pipelines for converting unstructured documents to structured formats such as XML, JSON, or proprietary schemas. - Developing and fine-tuning Conversational AI agents (chatbots, virtual assistants) for various use cases using Large Language Models (LLMs) or open-source models. - Training, evaluating, and deploying domain-specific AI/ML/NLP models. - Collaborating with product managers, domain experts, and backend/frontend engineers to integrate AI capabilities into production systems. - Leveraging frameworks like LangChain, Spring AI, or RAG pipelines for building intelligent systems. - Building tools and infrastructure to facilitate scalable and reusable AI model development. - Conducting comprehensive data preprocessing, feature engineering, and model performance evaluations. - Enabling Bring Your Own Model/AI capabilities for customers by designing pluggable AI interfaces. - Keeping abreast of the latest research and developments in the AI space. We are looking for candidates with the following qualifications: - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. - 8+ years of experience in Software Development. - 5+ years of professional experience in AI/ML/NLP. - Proven experience in Document AI, Conversational AI, model training and fine-tuning, strong programming skills in Python, and familiarity with Java/Kotlin-based backends. - Hands-on experience with frameworks like HuggingFace Transformers, LangChain, Spring AI, TensorFlow, PyTorch, or OpenAI API. - Experience with vector databases and semantic search, as well as familiarity with cloud platforms like Azure, AWS, or GCP. - Solid understanding of data privacy, model security, and ethical AI principles. Join Quark, a pioneer in closed-loop content lifecycle management, and be part of a team that enables organizations to engage their audiences with precision and impact. We offer comprehensive benefits from day one and are committed to your growth and success. Together, we will harness the power of innovative and successful content.,

By submitting your email address and any other personal information to this website, you consent to such information being collected, held, used and disclosed in accordance with our PRIVACY POLICY and our website TERMS AND CONDITIONS OUR STORY: At ContractPodAi, we&aposre pioneering the future of legal with Leahthe operating system for legal. Leah Agentic AI coordinates specialized AI agents across Leahs suite of solutions, including industry-leading Contract Lifecycle Management (CLM), to transform how legal teams work and create value. Leah doesn&apost just automate tasksit uncovers hidden opportunities and transforms legal knowledge into business advantage. Our platform breaks down silos between legal, business, and executive teams, helping organizations discover revenue opportunities, minimize risks, and turn legal insights into strategic decisions. We know innovation happens when great people come together to solve business problems. ContractPodAi is a fast-growing team of innovators spread across London, New York, Glasgow, San Francisco, Toronto, Dubai, Sydney, Mumbai, Pune, and beyond. Here, you&aposll: Pioneer the future of legal AI and business transformation Make real impact by helping organizations unlock hidden value Collaborate with talented colleagues across continents. If you&aposre excited by cutting-edge technology, thrive in a fast-paced environment, and want to help build something revolutionary, we want to hear from you. THE OPPORTUNITY We are seeking an experienced AI Engineer to join our growing team at ContractPodAi. In this role, you will design, develop, and deploy intelligent systems that power next-generation features in our contract lifecycle management (CLM) platform. You will work at the intersection of machine learning, software engineering, and agentic AI to create autonomous, goal-driven agents capable of reasoning, learning, and acting in dynamic environments. This is your opportunity to play a pivotal role in advancing the capabilities of legal tech with powerful agent-based systems built on the latest advancements in large language models, reinforcement learning, and autonomous AI frameworks. WHAT YOU WILL DO: Architect and implement scalable agentic AI systems that autonomously execute complex workflows and reason over legal data. Research, prototype, and productionize ML/DL models, especially in natural language processing and understanding (NLP/NLU). Build and deploy intelligent legal agents that can interpret documents, make decisions, and collaborate with users or other agents to complete multi-step tasks. Utilize modern frameworks and platforms (e.g., LangChain, LangGraph AutoGen, OpenAI Function Calling, Semantic Kernel) to build multi-agent workflows. Fine-tune and integrate large language models (LLMs) using PEFT, LoRA, and RAG techniques tailored to legal domain challenges. Design and implement robust infrastructure for managing AI lifecycle, including training, inference, monitoring, and continuous learning. Collaborate with legal experts, product managers, and engineering teams to create explainable and trustworthy AI systems. Contribute to the development of our AI strategy for agent-based automation within legal operations and contract management. WHAT YOU WILL NEED: 4+ Years of experience and a strong background in computer science, software engineering, or data science with a deep focus on machine learning and NLP. Demonstrated experience building or integrating agentic AI systems (e.g., AutoGPT-style agents, goal-oriented LLM pipelines, multi-agent frameworks). Proficiency in Python and ML/NLP libraries such as HuggingFace Transformers, LangChain, PyTorch, TensorFlow, and Spacy. Experience developing and scaling ML models (including LSTMs, BERT, Transformers) for real-world applications. Understanding of LLM training (e.g., OpenAI, LLAMA, Falcon), embeddings, and prompt engineering. Hands-on experience with Reinforcement Learning (e.g., PPO, RLHF, RLAIF). Experience extracting text and semantic information from structured and unstructured documents (PDFs, Images, etc.). Comfort working in Agile/Scrum environments and collaborating across cross-functional teams. Passion for innovation in AI and a strong desire to build autonomous systems that solve complex, real-world problems. BENEFITS: Competitive salary Opportunity to work in a fast-moving, high growth SaaS company Paid Time off Generous Employee Referral program At ContractPodAi we believe in creating a diverse and inclusive workplace where everyone feels heard and valued. We are proud to be an Equal Opportunity Employer. We do not discriminate in employment on the basis of race, color, religion, sex, national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor. Show more Show less

As a LLM Engineer at HuggingFace, you will play a crucial role in bridging the gap between advanced language models and real-world applications. Your primary focus will be on fine-tuning, evaluating, and deploying LLMs using frameworks such as HuggingFace and Ollama. You will be responsible for developing React-based applications with seamless LLM integrations through REST, WebSockets, and APIs. Additionally, you will work on building scalable pipelines for data extraction, cleaning, and transformation, as well as creating and managing ETL workflows for training data and RAG pipelines. Your role will also involve driving full-stack LLM feature development from prototype to production. To excel in this position, you should have at least 2 years of professional experience in ML engineering, AI tooling, or full-stack development. Strong hands-on experience with HuggingFace Transformers and LLM fine-tuning is essential. Proficiency in React, TypeScript/JavaScript, and back-end integration is required, along with comfort working with data engineering tools such as Python, SQL, and Pandas. Familiarity with vector databases, embeddings, and LLM orchestration frameworks is a plus. Candidates with experience in Ollama, LangChain, or LlamaIndex will be given bonus points. Exposure to real-time LLM applications like chatbots, copilots, or internal assistants, as well as prior work with enterprise or SaaS AI integrations, are highly valued. This role offers a remote-friendly environment with flexible working hours and a high-ownership opportunity. Join our small, fast-moving team at HuggingFace and be part of building the next generation of intelligent systems. If you are passionate about working on impactful AI products and have the drive to grow in this field, we would love to hear from you.,

As a member of our team, you will be responsible for applying NLP technologies to address business challenges. Your role will involve collaborating with different stakeholders within the organization to gain insights into the business problems at hand. Using your expertise in NLP, you will be developing solutions that leverage the latest technologies in this field. To excel in this position, you should have a solid foundation in statistics, machine learning, and deep learning specifically tailored for text and speech data. Your experience in natural language processing will be crucial as you engage in tasks such as textual data processing, training, and evaluating deep learning models including Transformer based models like Bert and GPT. We are looking for individuals with strong problem-solving abilities and proficiency in programming, particularly in Python. Familiarity with a range of NLP toolkits such as Langchain, LlamaIndex, Huggingface Transformers, Spacy, CoreNLP, OpenNLP will be advantageous. Additionally, experience in utilizing cloud services like AWS or Azure will be a valuable asset in this role.,

As an AI Developer specializing in Large Language Models (LLMs) at RMgX, a Gurgaon based digital product innovation & consulting firm, your role involves designing, developing, and deploying AI solutions using LLMs such as GPT, LLaMA, Claude, or Mistral. You will fine-tune and customize pre-trained LLMs for business-specific use cases, build and maintain NLP pipelines for classification, summarization, semantic search, etc., and create and manage vector database pipelines using tools like Milvus and Pinecone. Collaboration with cross-functional teams to integrate LLM-based features into applications and analyzing model performance to enhance outcomes will be key responsibilities. To excel in this role, you should have at least 12 years of experience in AI/ML development with a specific focus on NLP and LLM-based solutions. Proficiency in Python and AI/ML libraries such as HuggingFace Transformers, LangChain, PyTorch, TensorFlow, etc., is essential. Additionally, practical experience in working with closed-source models via APIs (e.g., OpenAI, Gemini), understanding of prompt engineering, embeddings, and vector databases like FAISS, Milvus, or Pinecone, and deploying models using REST APIs, Docker, and cloud platforms (AWS/GCP/Azure) are required. Familiarity with MLOps and version control tools (Git, MLflow, etc.), as well as knowledge of LLMOps platforms like LangSmith, Weights & Biases, will be advantageous. A Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field is preferred. Strong problem-solving skills, attention to detail, and the ability to work in an agile environment are crucial for success in this role. In return for your expertise and dedication, RMgX offers various perks and benefits, including flexible working hours, weekends off, health insurance, personal accident insurance, BYOD (Bring Your Own Device) benefit, and a laptop buyback scheme. Join us at RMgX to contribute to the creation of elegant, data-driven digital solutions for complex business problems and make a meaningful impact through your AI development skills.,

As a skilled and visionary AI Lead at Matellio, you will be responsible for driving the development of advanced AI solutions. This dual role will require you to provide technical leadership and hands-on development expertise, making it an ideal position for individuals who excel at solving complex problems using machine learning, NLP, and LLM technologies. Your key responsibilities will include leading and mentoring a team of 45 AI/ML engineers, overseeing the entire project lifecycle from research to production deployment. You will be tasked with designing and owning high-level and low-level architecture for AI and GenAI-based applications, ensuring scalability, performance, and maintainability. Collaboration with sales and business development teams to create technical proposals, solution designs, and architecture diagrams for Sales Qualified Leads (SQLs) will also be part of your role. Additionally, you will work as an individual contributor when necessary, focusing on developing key components of solutions to accelerate delivery and establish best practices. Your responsibilities will extend to researching, designing, and implementing machine learning and deep learning models, including fine-tuning and deploying LLMs like GPT and BERT for production use cases. Building NLP pipelines and retrieval-augmented generation (RAG) systems using tools such as LangChain, LangGraph, and vector databases like FAISS, Pinecone, and Weaviate will also be crucial. You will be expected to apply statistical techniques to feature engineering, model evaluation, and performance optimization, ensuring adherence to code quality, testing, CI/CD, and documentation standards. Staying up-to-date with the latest advancements in AI/ML and proposing innovative solutions will be essential. Conducting code reviews, promoting peer learning, and fostering a strong engineering culture will also be part of your responsibilities. To qualify for this role, you should hold a Bachelors, Masters, or Ph.D. in Computer Science, Engineering, Mathematics, or a related field. Additionally, you should have at least 7 years of hands-on experience in AI/ML model development and deployment. Proven expertise in leading technical teams and delivering production-grade AI/ML solutions is required. Strong architectural skills with experience in designing end-to-end solutions involving cloud, APIs, and ML models are essential. Proficiency in Python and ML libraries such as TensorFlow, PyTorch, and scikit-learn is necessary, along with hands-on experience in NLP tools like HuggingFace Transformers, SpaCy, and NLTK. Practical knowledge of fine-tuning and deploying LLMs, as well as building GenAI solutions, is expected. Familiarity with tools like LangChain, LangGraph, and vector stores (e.g., FAISS, Pinecone) will be advantageous. A solid understanding of classical ML algorithms (SVM, Decision Trees, etc.) and when to utilize them, experience deploying models and services using REST APIs, Docker, and CI/CD pipelines, and exposure to cloud platforms such as AWS, GCP, or Azure are highly desirable. Excellent analytical thinking, problem-solving, and communication skills will be crucial for success in this role.,

As an AI/ML Developer at our Gurugram location, you will be responsible for designing and implementing end-to-end machine learning models using Python for various tasks such as regression, classification, clustering, NLP, and deep learning. Your expertise in developing AI applications based on Machine Learning and Large Language Model (LLM) using tools like LangChain, RAG pipelines, vector databases, and more will be crucial in driving AI innovation. You will work on building and deploying AI applications leveraging technologies such as Retrieval Augmented Generation (RAG), LangChain, LLMs (OpenAI, Huggingface Transformers), and Vector Databases (FAISS, Pinecone, Milvus). Your role will involve developing robust pipelines for semantic search and retrieval chains in real-world production systems, writing clean and efficient Python code, and collaborating with cross-functional teams to deliver scalable AI/ML solutions. If you have front-end skills in React, it would be considered a big plus as you may also contribute to UI components for interactive AI applications. To be successful in this role, you should have at least 5 years of hands-on experience in AI/ML development using Python and a strong knowledge of ML algorithms such as XGBoost, SVM, Random Forests, Logistic Regression, as well as deep learning models like CNNs, RNNs, Transformers (BERT, GPT), and unsupervised learning techniques including K-Means and PCA. Experience with RAG architecture, LangChain, advanced prompt engineering, vector search techniques, and Python libraries like scikit-learn, TensorFlow, PyTorch, and Huggingface Transformers is essential. Proficiency in working with cloud environments such as AWS, Azure, or GCP is also required. It would be nice to have front-end development experience using React.js, familiarity with MLOps tools like MLflow, Kubeflow, Airflow, and knowledge of self-supervised or contrastive learning methods such as SimCLR and CLIP. In this role, you will have the opportunity to work on cutting-edge AI/ML technologies, collaborate in a fast-paced and innovative environment, contribute to impactful production-level AI solutions, and enjoy competitive compensation and benefits.,

AI/ML Development Leadership: Lead the implementation of machine learning models and automation pipelines for CPT/ICD code prediction and claims processing. Develop and optimize retrieval-augmented generation (RAG) workflows using LLMs, vector databases (e.g., FAISS), and custom prompts. Direct the design of structured training datasets derived from SOAP notes, payer files, and denial records. Team & Project Management: Manage day-to-day activities of India-based engineers and coding specialists. Coordinate closely with U.S.-based consultants to ensure AI solutions align with reimbursement policy and documentation standards. Track project milestones, guide model improvements, and ensure output quality. Technical Execution: Build, fine-tune, and deploy models using PyTorch, TensorFlow, HuggingFace Transformers , and scikit-learn . Integrate LLM APIs for code summarization and document understanding. Implement vector search and orchestration platforms for real-time AI assistance. Role & responsibilities Preferred candidate profile

As a skilled Data Scientist specializing in Generative AI, you will be responsible for designing, developing, and deploying state-of-the-art AI models to tackle real-world business challenges. Your role will involve working with Large Language Models (LLMs), Generative Adversarial Networks (GANs), Retrieval-Augmented Generation (RAG) frameworks, and transformer architectures to create production-ready solutions. Your key responsibilities will include: - Designing, developing, and fine-tuning advanced Generative AI models such as LLMs, GANs, and Diffusion models. - Implementing and enhancing RAG and transformer-based architectures to enable contextual understanding and document intelligence. - Customizing and optimizing LLMs for specific domain applications. - Building, maintaining, and optimizing ML pipelines and infrastructure for model training, evaluation, and deployment. - Collaborating with engineering teams to integrate AI models into user-facing applications. - Staying updated with the latest trends and research in Generative AI, open-source frameworks, and tools. - Analyzing model outputs for quality and performance, ensuring adherence to ethical AI practices. To excel in this role, you should possess the following skills: - Strong proficiency in Python and deep learning frameworks like TensorFlow, PyTorch, and HuggingFace Transformers. - Deep understanding of GenAI architectures such as LLMs, RAG, GANs, and Autoencoders. - Experience in fine-tuning models using techniques like LoRA, PEFT, or equivalents. - Knowledge of vector databases like FAISS, Pinecone, and embedding generation methods. - Experience in handling datasets, preprocessing, and synthetic data generation. - Solid grasp of NLP concepts, prompt engineering, and safe AI practices. - Hands-on experience in API development, model deployment, and cloud platforms such as AWS, GCP, and Azure. By leveraging your expertise in Generative AI and staying abreast of industry advancements, you will play a crucial role in developing cutting-edge solutions to address complex business problems.,

At PwC, our data and analytics team focuses on utilizing data to drive insights and support informed business decisions. We leverage advanced analytics techniques to assist clients in optimizing their operations and achieving strategic goals. As a data analysis professional at PwC, your role will involve utilizing advanced analytical methods to extract insights from large datasets, enabling data-driven decision-making. Your expertise in data manipulation, visualization, and statistical modeling will be pivotal in helping clients solve complex business challenges. PwC US - Acceleration Center is currently seeking a highly skilled MLOps/LLMOps Engineer to play a critical role in deploying, scaling, and maintaining Generative AI models. This position requires close collaboration with data scientists, ML/GenAI engineers, and DevOps teams to ensure the seamless integration and operation of GenAI models within production environments at PwC and for our clients. The ideal candidate will possess a strong background in MLOps practices and a keen interest in Generative AI technologies. With a preference for candidates with 4+ years of hands-on experience, core qualifications for this role include: - 3+ years of experience developing and deploying AI models in production environments, alongside 1 year of working on proofs of concept and prototypes. - Proficiency in software development, including building and maintaining scalable, distributed systems. - Strong programming skills in languages such as Python and familiarity with ML frameworks like TensorFlow and PyTorch. - Knowledge of containerization and orchestration tools like Docker and Kubernetes. - Understanding of cloud platforms such as AWS, GCP, and Azure, including their ML/AI service offerings. - Experience with continuous integration and delivery tools like Jenkins, GitLab CI/CD, or CircleCI. - Familiarity with infrastructure as code tools like Terraform or CloudFormation. Key Responsibilities: - Develop and implement MLOps strategies tailored for Generative AI models to ensure robustness, scalability, and reliability. - Design and manage CI/CD pipelines specialized for ML workflows, including deploying generative models like GANs, VAEs, and Transformers. - Monitor and optimize AI model performance in production, utilizing tools for continuous validation, retraining, and A/B testing. - Collaborate with data scientists and ML researchers to translate model requirements into scalable operational frameworks. - Implement best practices for version control, containerization, and orchestration using industry-standard tools. - Ensure compliance with data privacy regulations and company policies during model deployment. - Troubleshoot and resolve issues related to ML model serving, data anomalies, and infrastructure performance. - Stay updated with the latest MLOps and Generative AI developments to enhance AI capabilities. Project Delivery: - Design and implement scalable deployment pipelines for ML/GenAI models to transition them from development to production environments. - Oversee the setup of cloud infrastructure and automated data ingestion pipelines to meet GenAI workload requirements. - Create detailed documentation for deployment pipelines, monitoring setups, and operational procedures. Client Engagement: - Collaborate with clients to understand their business needs and design ML/LLMOps solutions. - Present technical approaches and results to technical and non-technical stakeholders. - Conduct training sessions and workshops for client teams. - Create comprehensive documentation and user guides for clients. Innovation And Knowledge Sharing: - Stay updated with the latest trends in MLOps/LLMOps and Generative AI. - Develop internal tools and frameworks to accelerate model development and deployment. - Mentor junior team members and contribute to technical publications. Professional And Educational Background: - Any graduate / BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Masters Degree / MBA,

Job Description: As a Data Scientist at Hitachi Solutions India Pvt Ltd in Pune, India, you will be a valuable member of our dynamic team. Your primary responsibility will be to extract valuable insights from complex datasets, develop advanced analytical models, and drive data-driven decision-making across the organization. With 8-14 years of experience, your primary skills should include Data Science, with secondary skills in Data Engineering/Data Analytics. You will play a pivotal role in working on cutting-edge AI applications with a focus on Natural Language Processing (NLP), Time Series Forecasting, and a working knowledge of Computer Vision (CV) techniques. Your role will involve collaborating with a diverse team of engineers, analysts, and domain experts to build holistic, multi-modal solutions. Your expertise in Python and libraries like Pandas, NumPy, Scikit-learn, HuggingFace Transformers, and Prophet/ARIMA will be essential. Additionally, you should have a strong understanding of the model development lifecycle, from data ingestion to deployment, and hands-on experience with SQL and data visualization tools like Seaborn, Matplotlib, and Tableau. Experience in handling retail-specific data, familiarity with cloud platforms like AWS, GCP, or Azure, and exposure to API development (FastAPI, Flask) for ML model deployment will be beneficial. Knowledge of MLOps practices, previous experience in fine-tuning language models, and expertise in Data Engineering using Azure technologies are desirable skills for this role. Key responsibilities will include applying NLP techniques to extract insights from text data, analyzing historical demand data for Time Series Forecasting, and potentially contributing to Computer Vision projects. Collaboration with cross-functional teams and developing scalable ML components for production environments will be crucial aspects of your role. Qualifications required for this position include a Master's degree in Computer Science, Data Science, Statistics, or a related field, proven experience in data science or machine learning, strong proficiency in Python and SQL, and familiarity with cloud technologies like Azure Databricks and MLflow. Excellent problem-solving skills, strong communication abilities, and the capability to work independently and collaboratively in a fast-paced environment are essential for success in this role. Please be cautious of potential scams during the recruitment process, and all official communication regarding your application and interview requests will be from our @hitachisolutions.com domain email address.,

As an AI Automation Specialist, you will play a crucial role in driving productivity optimization through the implementation of AI-powered solutions. Your responsibilities will include identifying opportunities to automate repetitive processes, enhance efficiency, and streamline workflows across various teams. You will be tasked with developing and executing automation strategies utilizing RPA, AI, and low-code/no-code tools to eliminate operational bottlenecks and enhance business operations. Collaborating closely with business leaders, product managers, and technology teams will be a key aspect of your role to drive AI transformation initiatives and ensure the successful scaling of automation impact. You will also be responsible for conducting change management activities, educating teams on AI-driven automation, and facilitating the seamless adoption of new processes within the organization. In addition, you will be involved in the deployment and management of AI tools such as NLP models, chatbots, document automation, and workflow optimization solutions. Working alongside cross-functional teams, you will assess pain points, design automation solutions, and implement AI-enabled productivity enhancements to drive continuous improvements and support strategic decision-making through data-driven analytics. Required Technical Skills: - Familiarity with low-code/no-code automation platforms like Bubble, Zapier AI, Make, Gumloop, n8n - Basic understanding of backend implementation including API integrations, Python, and JavaScript - Experience with video editing and graphic editing tools such as Heygen and Synthesia - Ability to build standalone apps using platforms like Replit and Lovable - Hands-on experience in NLP tools, chatbot development, and workflow automation - Strong understanding of data analytics and visualization tools like Power BI, Tableau, and Python - Proficiency in AI/ML tools (e.g., TensorFlow, Langgraph, HuggingFace Transformers) - Knowledge of AI tools for data science productivity (e.g., Cursor, Claude Code, H2O.ai, Windsurf, Copilot) Required Soft Skills: - Problem-solving mindset with the ability to identify inefficiencies and design AI-driven automation solutions - Leadership skills to influence senior leaders and drive impactful projects - Excellent communication and collaboration abilities to work effectively with cross-functional teams and stakeholders - Project management experience in implementing AI/automation projects with measurable impact.,

You are seeking a hands-on backend expert to elevate your FastAPI-based platform to the next level by developing production-grade model-inference services, agentic AI workflows, and seamless integration with third-party LLMs and NLP tooling. In this role, you will be responsible for various key areas: 1. Core Backend Enhancements: - Building APIs - Strengthening security with OAuth2/JWT, rate-limiting, SecretManager, and enhancing observability through structured logging and tracing - Adding CI/CD, test automation, health checks, and SLO dashboards 2. Awesome UI Interfaces: - Developing UI interfaces using React.js/Next.js, Redact/Context, and various CSS frameworks like Tailwind, MUI, Custom-CSS, and Shadcn 3. LLM & Agentic Services: - Designing micro/mini-services to host and route to platforms such as OpenAI, Anthropic, local HF models, embeddings & RAG pipelines - Implementing autonomous/recursive agents that orchestrate multi-step chains for Tools, Memory, and Planning 4. Model-Inference Infrastructure: - Setting up GPU/CPU inference servers behind an API gateway - Optimizing throughput with techniques like batching, streaming, quantization, and caching using tools like Redis and pgvector 5. NLP & Data Services: - Managing the NLP stack with Transformers for classification, extraction, and embedding generation - Building data pipelines to combine aggregated business metrics with model telemetry for analytics You will be working with a tech stack that includes Python, FastAPI, Starlette, Pydantic, Async SQLAlchemy, Postgres, Docker, Kubernetes, AWS/GCP, Redis, RabbitMQ, Celery, Prometheus, Grafana, OpenTelemetry, and more. Experience in building production Python REST APIs, SQL schema design in Postgres, async patterns & concurrency, UI application development, RAG, LLM/embedding workflows, cloud container orchestration, and CI/CD pipelines is essential for this role. Additionally, experience with streaming protocols, NGINX Ingress, SaaS security hardening, data privacy, event-sourced data models, and other related technologies would be advantageous. This role offers the opportunity to work on evolving products, tackle real challenges, and lead the scaling of AI services while working closely with the founder to shape the future of the platform. If you are looking for meaningful ownership and the chance to solve forward-looking problems, this role could be the right fit for you.,

At PwC, we focus on leveraging data to drive insights and make informed business decisions in the field of data and analytics. Our team utilises advanced analytics techniques to help clients optimize their operations and achieve their strategic goals. As a Data Analyst at PwC, you will play a crucial role in utilizing advanced analytical techniques to extract insights from large datasets and facilitate data-driven decision-making. Your responsibilities will include leveraging skills in data manipulation, visualization, and statistical modeling to assist clients in solving complex business problems. We are currently seeking a highly skilled MLOps/LLMOps Engineer to join PwC US - Acceleration Center. In this role, you will be responsible for the deployment, scaling, and maintenance of Generative AI models. Working closely with data scientists, ML/GenAI engineers, and DevOps teams, you will ensure seamless integration and operation of GenAI models within production environments at PwC and our clients. The ideal candidate will have a strong background in MLOps practices, coupled with experience and interest in Generative AI technologies. As a candidate, you should have a minimum of 4+ years of hands-on experience. Core qualifications for this role include 3+ years of experience developing and deploying AI models in production environments, with a year of experience in developing proofs of concept and prototypes. Additionally, a strong background in software development, proficiency in programming languages like Python, knowledge of ML frameworks and libraries, familiarity with containerization and orchestration tools, and experience with cloud platforms and CI/CD tools are essential. Key responsibilities of the role involve developing and implementing MLOps strategies tailored for Generative AI models, designing and managing CI/CD pipelines specialized for ML workflows, monitoring and optimizing the performance of AI models in production, collaborating with data scientists and ML researchers, and ensuring compliance with data privacy regulations. You will also be responsible for troubleshooting and resolving issues related to ML model serving, data anomalies, and infrastructure performance. The successful candidate will be proficient in MLOps tools such as MLflow, Kubeflow, Airflow, or similar, have expertise in generative AI frameworks, containerization technologies, MLOps and LLMOps practices, and cloud-based AI services. Nice-to-have qualifications include experience with advanced GenAI applications, familiarity with experiment tracking tools, knowledge of high-performance computing techniques, and contributions to open-source MLOps or GenAI projects. In addition to technical skills, the role requires project delivery capabilities such as designing scalable deployment pipelines for ML/GenAI models, overseeing cloud infrastructure setup, and creating detailed documentation for deployment pipelines. Client engagement is another essential aspect, involving collaboration with clients to understand their business needs, presenting technical approaches and results, conducting training sessions, and creating user guides for clients. To stay ahead in the field, you will need to stay updated with the latest trends in MLOps/LLMOps and Generative AI, apply this knowledge to improve existing systems and processes, develop internal tools and frameworks, mentor junior team members, and contribute to technical publications. The ideal candidate for this position should hold any graduate/BE/B.Tech/MCA/M.Sc/M.E/M.Tech/Masters Degree/MBA. Join us at PwC and be part of a dynamic team driving innovation in data and analytics!,