Jr AI engineer

As a Junior AI Engineer at Ve.ai, you will have the opportunity to contribute to the development and enhancement of cutting-edge AI models by applying concepts such as pattern recognition and neural networks. Your day-to-day tasks will involve designing, developing, and testing software solutions, implementing natural language processing (NLP) models, and collaborating with cross-functional teams to improve AI applications. Additionally, you will be involved in data analysis and algorithm optimization to ensure better performance. Key Responsibilities: - Develop and maintain AI-powered applications using Python and modern AI frameworks - Build and optimize RAG (Retrieval-Augmented Generation) systems - Design and implement prompt engineering workflows for improved AI responses - Work with LLMs (Large Language Models) for chatbot and AI assistant development - Design, monitor, and maintain scalable AI system infrastructure for high-performance model serving, API orchestration, and cloud-based AI workloads - Integrate and work with AI platforms and APIs including OpenAI, Anthropic Claude, and other Generative AI tools for building intelligent applications and AI agents - Optimize AI application deployment pipelines, resource utilization, and inference performance using cloud services such as AWS ECS, Lambda, and containerized environments - Evaluate and implement emerging AI tools, frameworks, and model providers to improve system capabilities, automation, and user experience Qualifications: - Experience in developing AI applications using Python and modern AI frameworks - Familiarity with building and optimizing RAG systems - Proficiency in designing prompt engineering workflows for improved AI responses - Knowledge of working with LLMs for chatbot and AI assistant development - Ability to design and maintain scalable AI system infrastructure - Experience in integrating and working with various AI platforms and APIs - Proficient in optimizing AI application deployment pipelines and resource utilization using cloud services - Ability to evaluate and implement emerging AI tools, frameworks, and model providers to enhance system capabilities and user experience As a Junior AI Engineer at Ve.ai, you will have the opportunity to contribute to the development and enhancement of cutting-edge AI models by applying concepts such as pattern recognition and neural networks. Your day-to-day tasks will involve designing, developing, and testing software solutions, implementing natural language processing (NLP) models, and collaborating with cross-functional teams to improve AI applications. Additionally, you will be involved in data analysis and algorithm optimization to ensure better performance. Key Responsibilities: - Develop and maintain AI-powered applications using Python and modern AI frameworks - Build and optimize RAG (Retrieval-Augmented Generation) systems - Design and implement prompt engineering workflows for improved AI responses - Work with LLMs (Large Language Models) for chatbot and AI assistant development - Design, monitor, and maintain scalable AI system infrastructure for high-performance model serving, API orchestration, and cloud-based AI workloads - Integrate and work with AI platforms and APIs including OpenAI, Anthropic Claude, and other Generative AI tools for building intelligent applications and AI agents - Optimize AI application deployment pipelines, resource utilization, and inference performance using cloud services such as AWS ECS, Lambda, and containerized environments - Evaluate and implement emerging AI tools, frameworks, and model providers to improve system capabilities, automation, and user experience Qualifications: - Experience in developing AI applications using Python and modern AI frameworks - Familiarity with building and optimizing RAG systems - Proficiency in designing prompt engineering workflows for improved AI responses - Knowledge of working with LLMs for chatbot and AI assistant development - Ability to design and maintain scalable AI system infrastructure - Experience in integrating and working with various AI platforms and APIs - Proficient in optimizing AI application deployment pipelines and resource utilization using cloud services - Ability to evaluate and implement emerging AI tools, frameworks, and model providers to enhance system capabilities and user experience