About the Role
Key Responsibilities:
Develop and manage the AI vision and strategic roadmap, aligning with the company’s overall business objectives.
Lead the design, implementation, and management of AI solutions to enhance business processes and customer experiences.
Collaborate with various back & front-end dev teams to integrate AI capabilities into existing and future business models and operations.
Project management to ensure successful deployment of AI projects, including setting clear goals, managing project deliverables, and ensuring timely execution.
Stay abreast of industry trends and developments in AI and machine learning to continuously innovate and improve our AI offerings.
Oversee the growth and development of the AI team, mentoring staff and managing resources effectively.
Ensure adherence to best practices in data governance, security, and compliance across all AI initiatives.
Requirements
As the Head of AI/ML, you will be instrumental in leading and executing our artificial intelligence & machine learning strategies to drive enterprise-level initiatives. This role requires a deep understanding of AI & ML & related technologies, such as:
Software Development: Proficiency in software development practices, version control systems (e.g., Git), and programming languages such as Python for building and maintaining the AI/ML platform.
Deep learning frameworks such as TensorFlow & PyTorch
Computer Vision concepts and techniques for tasks involving image processing, object detection, segmentation, and recognition
Generative Adversarial Networks (GANs): Knowledge of GAN architectures, training strategies, and techniques for stability and convergence is essential.
Image Processing: Proficiency in image processing techniques such as filtering, edge detection, and image enhancement for preprocessing and manipulating image data.
Natural Language Processing (NLP): Knowledge of NLP techniques such as text classification, sequence labeling, and language modeling can be beneficial.
Data Augmentation: Data augmentation techniques such as rotation, scaling, flipping, and color jittering for generating diverse training data and improving model generalization.
Model Evaluation and Optimization: Skills in model evaluation metrics, hyperparameter tuning, regularization techniques, and optimization algorithms for fine-tuning models and improving performance.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
Proven experience in a leadership role managing AI technologies and enterprise application architecture.
Strong technical background with hands-on experience in developing AI/ML solutions.
Demonstrable experience in developing and managing AI projects and strategies at an enterprise level.
Excellent analytical and problem-solving skills, with the ability to make data-driven decisions.
Strong leadership skills with experience in managing and growing teams.
Excellent communication and interpersonal skills to interact with stakeholders at all levels within the organization.