4 Zeroshot Learning Jobs

Techvantage Analytics is a fast-growing AI services and product engineering company specializing in Analytics, Machine Learning, and AI-based solutions. We are seeking a forward-thinking and highly experienced Gen AI Architect to design and implement cutting-edge AI solutions. The role involves leveraging the latest advancements in artificial intelligence and data science, including foundation models, multimodal AI, federated learning, and emerging AI frameworks. The ideal candidate will drive the development and deployment of scalable AI systems that power innovative applications across diverse domains. In this role, you will be responsible for AI Architecture Design, where you will develop robust architectures for generative AI solutions, leveraging the latest advancements in foundation models, large language models (LLMs), and multimodal AI. You will also be involved in Model Development, building and fine-tuning advanced generative models, such as GPT-based models, diffusion models, and transformers, for applications in text, image, video, and audio generation. Framework Integration is another key aspect of the role, where you will integrate modern AI frameworks, such as LangChain and LlamaIndex, to enhance the capabilities of generative models in production environments. Additionally, you will be tasked with implementing Data Strategy, including synthetic data generation, federated learning, and secure data sharing protocols for effective model training. You will design and oversee the deployment of scalable AI systems using the latest technologies, such as MLOps pipelines, container orchestration (Docker, Kubernetes), and serverless architectures. Ensuring Ethics & Compliance is also crucial, where you will make sure AI models comply with ethical guidelines, including responsible AI principles, addressing fairness, transparency, and mitigating bias. Staying updated with the latest AI trends, such as reinforcement learning with human feedback (RLHF), AI explainability, and continual learning, and applying them to real-world problems is essential. Collaboration is key in this role, as you will work closely with cross-functional teams, including data engineers, scientists, and product managers, to align AI systems with business goals. Leadership & Mentorship are also important aspects, as you will provide guidance to junior AI practitioners and foster a culture of innovation within the team. Performance Monitoring is another critical responsibility, where you will define KPIs for model performance, monitor systems in production, and implement mechanisms for continuous improvement and retraining. The ideal candidate for this role should have a Bachelors, Masters, or Ph.D. in Computer Science, Artificial Intelligence, Data Science, or related fields, along with 5+ years of experience in AI/ML, with a focus on generative AI technologies. Proven expertise in deploying large-scale generative models in production environments, hands-on experience with AI/ML frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers, and proficiency in Python, R, or Julia for data science and AI model development are required. Additionally, expertise in cloud-native AI solutions, familiarity with advanced data strategies like synthetic data creation and federated learning, and hands-on experience with MLOps practices are preferred. Strong analytical skills, the ability to thrive in a dynamic, fast-paced environment, and a proven track record of working effectively within cross-functional teams are also desired qualities in the ideal candidate.,

As a skilled AI Engineer, you will demonstrate proficiency in Generative AI & LLMs including GPT-3, Langchain, and LLMs. Your experience in prompt engineering, few-shot/zero-shot learning, RLHF, and model optimization will be essential in developing and implementing generative AI models. Your expertise in Machine Learning & NLP, particularly in Python utilizing frameworks like Hugging Face, TensorFlow, Keras, and PyTorch, will play a crucial role in optimizing LLM performance through fine-tuning and hyperparameter evaluation. A strong understanding of embeddings and data modeling is required for this role. Experience with various databases such as vector databases, RDBMS, MongoDB, and NoSQL databases (HBase, Elasticsearch), as well as data integration from multiple sources, will be beneficial. Your knowledge in Software Engineering, encompassing data structures, algorithms, system architecture, and distributed systems, will enable you to build and maintain robust distributed systems. Hands-on experience with Platform & Cloud technologies like Kubernetes, Spark ML, Databricks, and developing scalable platforms at scale is necessary. Proficiency in API Development, including API design, RESTful services, and data mapping to schemas, will be essential for integrating AI models into scalable web applications. Your responsibilities will include designing, developing, and implementing generative AI models, optimizing LLM performance, collaborating with ML and integration teams, building and maintaining distributed systems, integrating data from diverse sources, and enhancing response quality and performance using advanced techniques. To qualify for this role, you should hold a B.Tech / B.E. /M.Tech / M.E. degree and have a proven track record in building and deploying AI/ML models, particularly LLMs. Prior experience in developing public cloud services or open-source ML software would be advantageous. Knowledge of big-data tools will be considered a strong asset for this position.,

As an AIML - LLM Gen AI Engineer, your primary responsibility will be to design, develop, and implement solutions using transformer-based models for various Natural Language Processing (NLP) tasks. This includes tasks such as text generation, summarization, question answering, classification, and translation. You will be working extensively with transformer models like GPT, BERT, T5, RoBERTa, and similar architectures. Your deep understanding of model architectures, attention mechanisms, and self-attention layers will be crucial in effectively utilizing Large Language Models (LLMs) to generate human-like text. You will lead efforts in fine-tuning pre-trained LLMs and other transformer models on domain-specific datasets to optimize performance for specialized NLP tasks. In your role, you will apply your knowledge of attention mechanisms, context windows, tokenization, and embedding layers in model development and optimization. It will be essential to address and mitigate issues related to biases, hallucinations, and knowledge cutoffs that can impact LLM performance and output quality. You will craft clear, concise, and contextually relevant prompts to guide LLMs towards generating desired outputs, including the use of instruction-based prompting. Additionally, you will implement and experiment with zero-shot, few-shot, and many-shot learning techniques to maximize model performance without extensive retraining. Your iterative approach to prompt engineering strategies will involve refining outputs, rigorously testing model performance, and ensuring consistent and high-quality results. You will also be responsible for creating prompt templates for repetitive tasks that are adaptable to different contexts and inputs. Expertise in chain-of-thought (CoT) prompting will enable you to guide LLMs through complex reasoning tasks by encouraging step-by-step breakdowns. Your contribution will span the entire lifecycle of machine learning models in an NLP context, including training, fine-tuning, and deployment. **Required Skills & Qualifications:** - A minimum of 8 years of experience working with transformer-based models and NLP tasks, focusing on text generation, summarization, question answering, classification, and similar applications. - Proficiency in transformer models such as GPT, BERT, T5, RoBERTa, and foundational models. - Strong familiarity with model architectures, attention mechanisms, and self-attention layers for generating human-like text. - Proven experience in fine-tuning pre-trained models on domain-specific datasets for various NLP tasks. - Knowledge of attention mechanisms, context windows, tokenization, and embedding layers. - Awareness of biases, hallucinations, and knowledge cutoffs affecting LLM performance. - Ability to craft clear, concise, and contextually relevant prompts for LLMs. - Experience in zero-shot, few-shot, and many-shot learning techniques. - Proficiency in Python and NLP libraries like Hugging Face Transformers, SpaCy, NLTK. - Solid experience in training, fine-tuning, and deploying ML models in an NLP context. - Strong problem-solving skills and analytical mindset. - Excellent communication and collaboration abilities for remote or hybrid work environments. - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or related quantitative field. This role requires a combination of technical expertise in AI/ML, NLP, and transformer models, along with strong problem-solving and communication skills to achieve effective results in the field.,

Capgemini Invent is the digital innovation, consulting, and transformation brand of the Capgemini Group, a global business line that combines market-leading expertise in strategy, technology, data science, and creative design to help CxOs envision and build what's next for their businesses. In this role, you will be responsible for architecting and implementing advanced generative AI models with a focus on applications like image and text generation, content creation, and synthetic data generation. You will also be developing, fine-tuning, and optimizing these models to ensure they meet performance, scalability, and business objectives. Applying solid data science principles, you will enhance AI/ML models using statistical analysis and machine learning techniques to improve accuracy and efficiency. Collaboration with data engineers, software developers, and product managers will be crucial to integrating generative AI models into products and services, aligning with business objectives. Staying updated with the latest advancements in AI/ML and generative AI, you will drive the adoption of new technologies and best practices within the team. Furthermore, you will be responsible for ensuring ethical AI implementation by designing and deploying AI models with ethical considerations, adhering to industry standards, and regulatory requirements. To be successful in this role, you should possess a bachelor's or master's degree in computer science, AI, Machine Learning, Data Science, or a related field, along with 5+ years of experience in AI/ML, particularly with generative AI models. Strong expertise in developing and deploying generative AI models, proficiency in Python, and experience with AI development libraries such as TensorFlow and PyTorch are required. Additionally, familiarity with advanced techniques like Retrieval-Augmented Generation (RAG), fine-tuning, prompt engineering, and zero-shot learning will be beneficial. Domain knowledge in NLP or computer vision related to generative AI applications is also desired. At Capgemini, we value flexible work arrangements to support a healthy work-life balance, whether through remote work or flexible work hours. Our career growth programs and diverse professions are designed to help you explore a world of opportunities. You will have the opportunity to equip yourself with valuable certifications in the latest technologies such as Generative AI. Capgemini is a global business and technology transformation partner with a strong heritage trusted by clients worldwide. Our team members in over 50 countries work together to accelerate the dual transition to a digital and sustainable world, creating tangible impact for enterprises and society. We offer end-to-end services and solutions leveraging strengths in AI, cloud, and data, combined with deep industry expertise and a strong partner ecosystem. Join us in unlocking the value of technology to address a wide range of business needs.,