Generative AI Engineer

Company Description Stack AI Solutions is a technology company specializing in Generative AI, Computer Vision, and end-to-end Mobile and Web application development. By combining advanced artificial intelligence techniques with robust software engineering, the company delivers intelligent products and services that help clients innovate and scale in the digital era. Stack AI Solutions partners with organizations to build tailored solutions that address complex business challenges and unlock new opportunities. The team is committed to pushing the boundaries of emerging technologies and actively contributes to shaping the future of AI-driven software.Role Description This is a full-time, on-site Generative AI Engineer role based in Hyderabad. The Generative AI Engineer will design, develop, and deploy AI models and pipelines, focusing on generative techniques such as large language models, diffusion models, and multimodal systems. Daily responsibilities include collaborating with product and engineering teams to translate business requirements into model specifications, implementing and optimizing training and inference workflows, and integrating AI components into mobile and web applications. The role involves conducting experiments, evaluating model performance, improving reliability and scalability in production, and documenting architectures and best practices. The engineer will also stay current with advances in AI research and tools, and contribute to internal frameworks and reusable components.QualificationsStrong foundation in machine learning and deep learning, including experience with Generative AI models (e.g., LLMs, transformers, autoencoders, diffusion models).Proficiency in programming for AI development, including Python and relevant frameworks such as PyTorch or TensorFlow.Experience building and deploying AI services, including APIs, microservices, and integration with web or mobile applications.Knowledge of data engineering practices, such as data preprocessing, feature engineering, and working with large-scale datasets.Familiarity with cloud platforms and MLOps tools (e.g., Docker, Kubernetes, CI/CD, model monitoring, and versioning).Understanding of computer vision or NLP techniques and their application in real-world products is highly beneficial.Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience.Ability to work collaboratively in cross-functional teams, communicate technical concepts clearly, and document solutions and processes.Experience in performance optimization, model evaluation, and responsible AI practices (fairness, robustness, security, and privacy) is a plus.Interest in continuous learning, staying updated with AI research, and contributing to internal knowledge sharing and innovation.