Senior AI Engineer / AI Lead Engineer

As a Lead - AI Engineer at Xerago, you will play a crucial role in driving our mission for customer immortality. Your responsibilities will include managing a team of AI engineers, developing high-quality AI models with strong predictive accuracy, and staying updated on the latest technologies in the field. By collaborating closely with project stakeholders, you will shape AI strategies, oversee timelines, and contribute significantly to the success and growth of our organization. Your influence will extend to our digital impact initiatives, shaping the future of technology at Xerago. In terms of technical responsibilities, you will be responsible for designing, developing, and implementing AI models using Python, TensorFlow, or PyTorch to ensure robustness and accuracy. Collaboration with the data team to clean, manipulate, and analyze large datasets using NumPy, Pandas, or similar libraries will be a key aspect of your role. Additionally, you will oversee the deployment of AI solutions on cloud platforms such as AWS, Google Cloud, or Microsoft Azure to optimize performance and efficiency. On the managerial front, you will lead and mentor a team of AI engineers, providing technical guidance and fostering a culture of continuous learning. Coordination with project stakeholders to define AI strategies, manage timelines, and ensure the successful delivery of AI-driven solutions will also fall within your purview. To qualify for this role, you should hold a Bachelor's degree in Computer Science, Information Technology, Machine Learning, or a related field with a strong focus on AI and machine learning. Expertise in Python programming languages, deep learning frameworks like TensorFlow or PyTorch, and data manipulation libraries such as NumPy and Pandas is essential. Proficiency in cloud platforms such as AWS, Google Cloud, or Microsoft Azure is a prerequisite, while familiarity with data visualization tools (e.g., Matplotlib, Seaborn) and version control systems (e.g., Git) is desired. Although not mandatory, certifications such as Google Professional Machine Learning Engineer, AWS Certified Machine Learning Specialty, Microsoft Certified: Azure AI Engineer Associate, and TensorFlow Developer Certificate by Deeplearning.ai are considered valuable. Strong communication, leadership, team management, adaptability, problem-solving, and strategic thinking abilities are crucial for success in this role. This is a full-time position with a work schedule of Monday to Friday, requiring in-person presence at the designated work location.,