7 Multimodal Ai Jobs

As an Assistant Vice President Generative AI Systems Architect, you will leverage your 12+ years of experience to architect and design end-to-end systems for production-grade Generative AI applications. This includes creating systems for LLM-based chatbots, copilots, and content generation tools. Your responsibilities will involve defining system architecture for data ingestion, model training/fine-tuning, inferencing, and deployment pipelines. It is essential to establish architectural tenets such as modularity, scalability, reliability, observability, and maintainability. Collaboration plays a crucial role in this role, as you will work closely with data scientists, ML engineers, platform engineers, and product managers to ensure that the architecture aligns with both business objectives and AI goals. Your tasks will include choosing and integrating foundation models, evaluating solutions based on various architecture patterns, and designing secure and compliant architectures for enterprise settings, focusing on data governance, auditability, and access control. Additionally, you will lead system design reviews, define non-functional requirements (NFRs) like latency, availability, throughput, and cost, and collaborate with MLOps teams to establish CI/CD processes for model and system updates. Your contribution to creating reference architectures, design templates, and reusable components will be valuable in driving efficiency and consistency across projects. To excel in this role, it is important to stay updated with the latest advancements in GenAI, system design patterns, and AI platform tooling. Your role as an Assistant Vice President Generative AI Systems Architect will be dynamic and impactful, contributing significantly to the advancement and implementation of cutting-edge AI technologies.,

As a Senior Machine Learning Engineer at TrueFan, you will be at the forefront of AI-driven content generation, leveraging cutting-edge generative models to build next-generation products. Your mission will be to redefine the content generation space through advanced AI technologies, including deep generative models, text-to-video, image-to-video, and lipsync generation. Your responsibilities will include designing, developing, and deploying cutting-edge models for end-to-end content generation. This will involve working on the latest advancements in deep generative modeling to create highly realistic and controllable AI-generated media. You will research and develop state-of-the-art generative models such as Diffusion Models, 3D VAEs, and GANs for AI-powered media synthesis. Additionally, you will build and optimize AI pipelines for high-fidelity image/video generation and lipsyncing using diffusion and autoencoder models. Furthermore, you will be responsible for developing advanced lipsyncing and multimodal generation models that integrate speech, video, and facial animation for hyper-realistic AI-driven content. Your role will also involve implementing and optimizing models for real-time content generation and interactive AI applications using efficient model architectures and acceleration techniques. Collaboration with software engineers to deploy models efficiently on cloud-based architectures will be a key aspect of your work. To qualify for this role, you should have a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field, along with 3+ years of experience working with deep generative models like Diffusion Models, 3D VAEs, GANs, and autoregressive models. Proficiency in Python and deep learning frameworks such as PyTorch is essential. Strong problem-solving abilities, a research-oriented mindset, and familiarity with generative adversarial techniques are also required. Preferred qualifications include experience with transformers and vision-language models, background in text-to-video generation and lipsync generation, expertise in cloud-based AI pipelines, and contributions to open-source projects or published research in AI-generated content. If you are passionate about AI-driven content generation and have a strong background in generative AI, this is the perfect opportunity for you to drive research and development in AI-generated content and real-time media synthesis at TrueFan.,

As a Senior Machine Learning Engineer, you will have the exciting opportunity to be involved in designing, developing, and deploying cutting-edge models for end-to-end content generation. This includes working on AI-driven image/video generation, lip syncing, and multimodal AI systems. You will be at the forefront of the latest advancements in deep generative modeling, striving to create highly realistic and controllable AI-generated media. Your responsibilities will encompass researching and developing state-of-the-art generative models like Diffusion Models, 3D VAEs, and GANs for AI-powered media synthesis. You will focus on building and optimizing AI pipelines for high-fidelity image/video generation and lip syncing. Additionally, you will be tasked with developing advanced lip-syncing and multimodal generation models that integrate speech, video, and facial animation for hyper-realistic AI-driven content. Implementing and optimizing models for real-time content generation and interactive AI applications using efficient model architectures and acceleration techniques will also be part of your role. Collaboration with software engineers to deploy models efficiently on cloud-based architectures (AWS, GCP, or Azure) will be crucial. Staying updated with the latest trends in deep generative models, diffusion models, and transformer-based vision systems to enhance AI-generated content quality will be an essential aspect of the role. Furthermore, designing and conducting experiments to evaluate model performance, improve fidelity, realism, and computational efficiency, as well as refining model architectures will be expected. Active participation in code reviews, improving model efficiency, and documenting research findings to enhance team knowledge-sharing and product development will also be part of your responsibilities. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field. You should have a minimum of 3 years of experience working with deep generative models, such as Diffusion Models, 3D VAEs, GANs, and autoregressive models. Proficiency in Python and deep learning frameworks like PyTorch is essential. Expertise in multi-modal AI, text-to-image, and image-to-video generation, as well as audio to lip sync, is required. A strong understanding of machine learning principles and statistical methods is necessary. It would be beneficial to have experience in real-time inference optimization, cloud deployment, and distributed training. Strong problem-solving abilities and a research-oriented mindset to stay updated with the latest AI advancements are qualities that would be valued. Familiarity with generative adversarial techniques, reinforcement learning for generative models, and large-scale AI model training will also be beneficial. Preferred qualifications include experience with transformers and vision-language models (e.g., CLIP, BLIP, GPT-4V), a background in text-to-video generation, lip-sync generation, and real-time synthetic media applications, as well as experience in cloud-based AI pipelines (AWS, Google Cloud, or Azure) and model compression techniques (quantization, pruning, distillation). Contributions to open-source projects or published research in AI-generated content, speech synthesis, or video synthesis would be advantageous.,

As a Senior Machine Learning Engineer, your primary role will involve designing, developing, and deploying advanced models for end-to-end content generation. This includes AI-driven image/video generation, lip syncing, and multimodal AI systems. Your focus will be on leveraging cutting-edge deep generative modeling techniques to produce highly realistic and controllable AI-generated content. You will be responsible for researching and developing state-of-the-art generative models, such as Diffusion Models, 3D VAEs, and GANs, to power AI-driven media synthesis. Additionally, you will work on building and optimizing AI pipelines for high-fidelity image/video generation and lip syncing using diffusion and autoencoder models. Your expertise will also be utilized in developing advanced lip-syncing and multimodal generation models that integrate speech, video, and facial animation for hyper-realistic AI-driven content. In addition to model development, you will implement and optimize models for real-time content generation and interactive AI applications. Collaboration with software engineers to efficiently deploy models on cloud-based architectures (AWS, GCP, or Azure) will be a key aspect of your role. Staying updated on the latest trends in deep generative models, diffusion models, and transformer-based vision systems will be essential to enhance the quality of AI-generated content. Your responsibilities will include designing and conducting experiments to evaluate model performance, improve fidelity, realism, and computational efficiency. Participation in code reviews, enhancing model efficiency, and documenting research findings for team knowledge-sharing will also be part of your duties. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field, along with at least 3 years of experience working with deep generative models. Proficiency in Python and deep learning frameworks like PyTorch is required. Expertise in multi-modal AI, text-to-image, image-to-video generation, and audio to lip sync is essential. A strong understanding of machine learning principles, statistical methods, and problem-solving abilities are also necessary. Additionally, experience with transformers, vision-language models, cloud-based AI pipelines, and model compression techniques is advantageous. Contributions to open-source projects or published research in AI-generated content, speech synthesis, or video synthesis will be beneficial. This position offers a dynamic opportunity to work on cutting-edge AI technologies and collaborate with a team of experts in the field. If you are passionate about pushing the boundaries of AI-generated content and staying at the forefront of AI advancements, this role is ideal for you.,

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