AI Solution Architect

As the AI Solutions Architect, you will be responsible for designing and implementing AI/ML solutions to advance the ZL Platform. Your role involves collaborating with stakeholders to identify business needs, proposing technical solutions, and overseeing the implementation of the chosen solutions. You will partner with Engineering, Product, and Sales teams to secure design wins at customers, enabling the development and growth of ZL product features through customer feedback and PoC evaluations. Additionally, you will be accountable for the success, quality, and timely delivery of AI/ Machine Learning components. Acting as a problem solver, you will address organizational and process challenges by leveraging your technical expertise to bridge gaps, streamline operations, and facilitate the smooth execution of partnership initiatives. It is crucial to stay updated on AI and Data Engineering trends to enhance team performance and product quality. In terms of qualitative expectations, you are expected to foster a culture of innovation, continuous improvement, and excellence in software development. You should take ownership of problems, acquire necessary knowledge, and demonstrate the ability to work efficiently in an environment with loosely defined tasks and competing priorities. Collaboration with various teams within the organization, including Engineering/Research, Sales, Product, and Marketing, is essential. Effective verbal and written communication skills, as well as technical presentation abilities, are key requirements. A self-starter mindset with a passion for growth, enthusiasm for continuous learning, and the ability to share findings across the team are highly valued qualities. The ideal candidate should have experience working in AI/ML for over 10 years, preferably with vector databases, and possess a PhD or master's degree in computer science, Artificial Intelligence, or related disciplines. Knowledge of libraries such as PyTorch and transformers, quantization, model deployment, and fine-tuning LLM using PyTorch is preferred for this role.,