4 Multimodal Ai Jobs

We are seeking a highly skilled LLM Engineer with deep expertise in chatbot implementations and large language models (LLMs) . The ideal candidate should have hands-on experience with Retrieval-Augmented Generation (RAG) , instruction fine-tuning , parameter-efficient fine-tuning (PEFT) techniques such as LoRA or QLoRA , and proficiency in frameworks like LangChain , LlamaIndex , Haystack , Rasa , or their equivalents. The role requires experience in designing and implementing at least two chatbot projects end-to-end, coupled with a strong understanding of requirement analysis, architecture planning , and solution strategy formulation . Bonus points for experience with Vision-Language Models (VLMs) and multimodal AI applications integrating text, image, video, and audio data. Key Responsibilities Design, architect, and develop intelligent chatbot systems using state-of-the-art LLM techniques. Analyze business and functional requirements and translate them into scalable LLM solutions. Implement Retrieval-Augmented Generation (RAG) pipelines using relevant libraries and vector databases. Apply instruction fine-tuning and PEFT techniques like LoRA/QLoRA for domain-specific customization. Build LLM applications using frameworks such as LangChain , LlamaIndex , Haystack , or Rasa . Integrate chatbots with enterprise systems, APIs, and document stores. Work with vector databases (e.g., Pinecone, FAISS, Weaviate, ChromaDB) and embedding models. Collaborate cross-functionally with design, product, and engineering teams for integration and deployment. (Preferred) Develop multimodal systems that process combinations of text, audio, video, and images. Stay up to date with the latest research in conversational AI, LLMs, and multimodal AI. Document technical architecture, processes, and best practices. Required Qualifications Bachelor's or Masters in Computer Science, Artificial Intelligence, Data Science, or equivalent. 6 to 9 years of total experience in software/AI development with minimum 2+ chatbot projects delivered using LLMs. Proficiency in RAG , instruction tuning , and parameter-efficient fine-tuning (LoRA/QLoRA) techniques. Strong expertise in one or more frameworks: LangChain , LlamaIndex , Haystack , Rasa , etc. Solid programming skills in Python and familiarity with Transformers , PyTorch , or TensorFlow . Experience with vector databases , embedding models , and NLP pipelines . Ability to understand business needs and independently drive solution strategy and implementation. Excellent communication and stakeholder engagement skills. Preferred Qualifications Exposure to multimodal AI and Vision-Language Models (VLMs) such as Flamingo, GPT-4V, or Kosmos. Experience with MLOps tools and deploying LLMs into scalable production environments. Understanding of prompt engineering, few-shot learning, and performance optimization for LLMs. Familiarity with model evaluation metrics specific to conversational and generative tasks. Soft Skills Strong analytical and problem-solving mindset. Self-motivated, with the ability to take initiative and ownership. Effective communicator with the ability to translate complex technical concepts into business outcomes. Comfortable working in agile, fast-paced environments.

Job Description Greetings from Fujitsu Research Lab (https://www.fujitsu.com/global/about/research/) About us: At Fujitsu AI Lab, we are at the forefront of research, innovation, and product development in areas such as AI (artificial intelligence), Machine Learning (ML), and Data Science. Our technologies are integrated into Fujitsus products and customer systems across sectors like finance, telecommunications, manufacturing, healthcare, and social infrastructure. We are committed to shaping the future with cutting-edge AI research, driving advancements in fields such as Generative AI, Cognitive AI, Graph ML, ML models for complex temporal and multimodal data. Role Purpose: As an AI Researcher, you will lead groundbreaking research aligned with Fujitsu's AI strategy. Your work will directly influence product innovations and the development of novel AI technologies. Additionally, you will drive scientific exploration, publish in top-tier conferences and journals, and secure patents for innovative work. Roles and Responsibilities- Followings are Researchers duties: Technical Skills required- Advanced AI/ML Expertise : Deep understanding of fundamentals of theoretical machine learning, statistical theory of learning, AI related topics and concepts, and their practical implementation in various domains. Up to date with the latest in AI algorithms & neural architectures ( e.g. , attention, transformers, state-space models, etc.), and their application in discriminative and generative models, explainable AI, causal reasoning, knowledge representation, concept discovery & extraction, continual learning, etc. Prior experience in applying them to one or more of the following areas or related topics: natural language (LLMs), human cognition, computer vision, point cloud, graphs, multi-modal data analytics, time-series, sequence modelling, complex task completion, dynamic optimization etc . Proficient in AI/ML Programming : Advanced skills in coding, working with AI/ML libraries, and familiar with major AI platforms and tools. Strong publication track in top-tier conferences such as ICML, ICLR, NeurIPS, AAAI, IJCAI, AISTATS, SIGKDD, ACL, NAACL etc. For computer vision domain, publications in top CV conferences like CVPR, ICCV, ECCV is expected. Desirable: Well-informed with latest conceptual advancements in the deployable AI framework (such as AI agents, autonomous systems etc .). Core Research Leadership Identify and Frame Research Problems : Brainstorm with other researchers to scope new research projects in specified areas. Identifies critical research challenges and develop innovative solutions by differentiating your approaches from the current state of the art. Develop Advanced Technologies : Design new algorithms, neural architectures, and computing methodologies. Implement and validate through theoretical and experimental research. Conduct Rigorous Data Analysis : Collect and analyze data to draw inferences, support proposed solutions, and demonstrate their practical applications. Collaboration & Knowledge Sharing Share key findings with internal leadership, including Project Leaders, Research Managers, and Project Directors. Research Publication & IP : Draft and submit patents. Author research papers for submission to prestigious AI/ML/CV/NLP conferences and journals. Academic Partnerships : Engage with academic institutions and collaborators, expanding Fujitsus network and promoting cutting-edge AI research. Industry Impact and Application Engage with Applied Research Teams : Collaborate closely with applied researchers to transform core scientific discoveries into practical solutions. Abstract complex research problems from real-world challenges. Support Technology Transition : Facilitate the transfer of research outcomes to business units, demonstrating their value to external clients and driving real-world impact. Additional Expectations Scientific Leadership : Strong vision for research and the ability to lead scientific projects towards impactful breakthroughs. Communication : Exceptional communication, report writing, and presentation skills, with the ability to translate complex research into understandable and actionable insights. Adaptability and Growth Mindset : Willingness to learn new fields, explore uncharted territories in AI, and develop cross-disciplinary skill sets. Education & Research Experience : Ph.D. in AI, Machine Learning, Computer Science, or a related field with a research experience of 3-10 years (post PhD). Person with more experience will be considered for appropriate positions.

Job Overview : This is a Full-time role for a Generative AI Engineers for our client in Software Development, in Bangalore/Bengaluru, Karnataka. We are seeking a talented and experienced Generative AI Engineer to join our client team. The ideal candidate will have a strong background in artificial intelligence, machine learning, and programming with a focus on generative models. You will be responsible for designing, developing, and implementing cutting-edge generative AI solutions to solve complex problems and enhance our clients products and services. As part of a cross-functional engineer, you'll work closely with project managers, and DevOps professionals to enhance functionality, optimize workflows, and deliver high-quality Software. Success in this role is measured through key performance indicators (KPIs) such as System Performance, Code Quality, Team Effectiveness, Project Success. Role & responsibilities Design/develop multi-agent AI systems, architect RAG system/knowledge graphs Create proper engineering frameworks Build orchestration systems Implement generative AI techniques Collaborate on custom AI solutions Maintain scalable cloud AI Infrastructure Required Skills & Qualifications : Graduate/ Masters in Computer Science/AI related streams; model skills fine-tuning experience; multimodal AI knowledge; containerization/orchestration skills 3-5 years generative AI/LLM experience; expert Python skills; experience with LLM frameworks, multi-agent systems, vector databases; cloud proficiency (AWS, GCP, Azure) Compensation and Benefits: Base Salary: Competitive salary range based on experience and performance. Bonuses & Incentives: Performance-based bonuses. Health & Wellness: Comprehensive medical insurance. Career Growth: Ongoing training programs, professional development courses, mentorship opportunities, and career advancement prospects. Immediate joiner within 15 days 30 days notice period

About the Role: We are seeking a highly skilled Lead Data Scientist with 4-8 years of experience to drive innovation in machine learning, deep learning, and generative AI. The ideal candidate should have expertise in Large Language Models (LLM), Retrieval-Augmented Generation (RAG), AI Agents, and hands-on experience in LangChain or LlamaIndex, and Knowledge Graphs. The role also requires strong technical leadership and experience in AI Agent frameworks and libraries. Key Responsibilities: Lead the development and deployment of machine learning models, deep learning frameworks, and AI-driven solutions across the organization. Work closely with stakeholders to define data-driven strategies and drive innovation using AI and machine learning. Design and implement robust data pipelines and workflows in collaboration with data engineers and software developers. Develop and deploy APIs using web frameworks for seamless integration of AI/ML models into production environments. Mentor and lead a team of data scientists and engineers, providing technical guidance and fostering professional growth. Leverage LangChain or LlamaIndex to enhance model integration, document management, and data retrieval capabilities. Lead projects in Generative AI technologies, such as Large Language Models (LLM), Retrieval-Augmented Generation (RAG), and AI agents, to create innovative AI-driven products and services. Stay updated on the latest AI/ML trends, ensuring that cutting-edge methodologies are adopted across projects. Collaborate with cross-functional teams to translate business problems into technical solutions and communicate findings effectively to both technical and non-technical stakeholders. Required Skills and Qualifications: Experience: 4-8 years of experience in data science and AI/ML, with a strong foundation in machine learning, deep learning, generative AI and data engineering. Generative AI Expertise: Minimum 2 years of experience with gneretaive AI. Hands-on experience with LLMs, RAG, and AI agents. AI Agents & Frameworks: Hands-on experience with AI agent frameworks/libraries (e.g., LangGraph, CrewAI, OpenAI's Function Calling, Semantic Kernel, etc.). Programming: Strong proficiency in Python, with experience using TensorFlow, PyTorch, and Scikit-learn. LangChain & LlamaIndex: Experience integrating LLMs with structured and unstructured data. Knowledge Graphs: Expertise in building and utilizing Knowledge Graphs for AI-driven applications. SQL & NoSQL Databases: Hands-on experience with SQL (PostgreSQL, MySQL, etc.) and NoSQL (MongoDB, Cassandra, etc.) database. API Development: Experience in developing APIs using Flask or FastAPI or Django. Cloud & MLOps: Experience working with cloud providers like AWS, GCP, Azure and MLOps best practices. Excellent communication, leadership, and project management skills. Strong problem-solving ability with a focus on delivering scalable, impactful solutions. Preferred Skills: Experience with Computer Vision applications. Chain of Thought Reasoning: Familiarity with CoT prompting and reasoning techniques. Ontology: Understanding of ontologies for knowledge representation in AI systems. Data Engineering: Experience with ETL pipelines and data engineering workflows. Familiarity with big data tools like Spark, Hadoop, or distributed computing.