Generative AI Engineer

ideyaLabs is looking for a talented and innovative Generative AI Engineer with experience in utilizing Low-Code/No-Code (LCNC) platforms. In this role, you will play a key part in developing and deploying cutting-edge generative AI models while leveraging LCNC tools to accelerate prototyping, integration, and application development. The ideal candidate should have a strong understanding of generative AI techniques, programming proficiency, and a keen interest in exploring the synergy between AI and rapid application development. Responsibilities Generative AI Model Development & Deployment: - Design, develop, train, and evaluate generative AI models for various applications such as text generation, image synthesis, code generation, and synthetic data generation. - Implement and optimize generative AI models using frameworks like TensorFlow, PyTorch, and Transformers. - Deploy and scale generative AI models on cloud platforms such as AWS, Azure, GCP, or on-premise infrastructure. - Stay updated with the latest advancements in generative AI research and techniques. Low-Code/No-Code Platform Utilization: - Utilize LCNC platforms like Zoho Creator, Microsoft Power Apps, OutSystems, Mendix, and Quixy to rapidly prototype and build applications integrating generative AI models. - Develop user interfaces and workflows using LCNC visual development tools. - Connect generative AI APIs and services to LCNC applications. - Build and deploy data connectors and integrations between systems using LCNC capabilities. Integration & Application Development: - Design and implement robust APIs and integration strategies to connect generative AI models with other systems and applications. - Collaborate with software engineers and data scientists to build end-to-end AI-powered solutions. - Develop and maintain documentation for AI models, LCNC applications, and integration processes. Experimentation & Innovation: - Research and experiment with new generative AI models, LCNC platforms, and integration techniques. - Evaluate the feasibility of applying generative AI to solve specific business problems. - Contribute to developing best practices and guidelines for using generative AI and LCNC tools. Collaboration & Communication: - Work closely with cross-functional teams, including product managers, designers, and business stakeholders. - Communicate technical findings and progress effectively to both technical and non-technical audiences. - Participate in code reviews and knowledge-sharing activities. Qualifications Education: - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience: - 3+ years of experience in developing and deploying machine learning models, focusing on generative AI. - Proven experience with at least one or more Low-Code/No-Code development platforms. - Experience in building and consuming APIs (RESTful, etc.). Technical Skills: - Strong programming skills in Python and experience with AI/ML libraries like TensorFlow, PyTorch, scikit-learn, and Transformers. - Solid understanding of deep learning concepts and architectures relevant to generative models such as GANs, VAEs, Diffusion Models, and Transformers. - Experience with cloud platforms like AWS, Azure, GCP and their AI/ML services. - Familiarity with data preprocessing, feature engineering, model evaluation techniques, database concepts, SQL, visual development tools, and integration capabilities of LCNC platforms. Soft Skills: - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. - Quick learner with an ability to adapt to new technologies. - Proactive, self-motivated, with a sense of ownership. - Passion for innovation and exploring the potential of generative AI. Preferred Qualifications: - Experience with specific generative AI applications relevant to the industry. - Familiarity with containerization technologies like Docker, Kubernetes. - Experience with MLOps practices and tools. - Certifications in relevant AI/ML or LCNC platforms.,