Director, AI/ML Technology and Architecture

Define and evolve the long-term AI/ML architecture roadmap, ensuring scalability, maintainability, and integration with existing systems.

Conduct thorough technology evaluations and vendor assessments to identify and select the most suitable AI/ML tools, platforms, and technologies.

Develop and implement best practices, guidelines, and standards for AI/ML development and deployment across the organization.

Collaborate with business stakeholders to understand their needs and translate them into clear and actionable AI/ML strategies.

Drive innovation by exploring and evaluating emerging AI/ML technologies and their potential applications within the media and entertainment domain.

Design, build, and maintain a robust and scalable AI/ML platform that supports the entire lifecycle of AI/ML model development, from data ingestion and feature engineering to model training, deployment, and monitoring.

Ensure the security, reliability, and performance of the AI/ML infrastructure, including data privacy, compliance, and disaster recovery.

Optimize resource utilization and cost-effectiveness of the AI/ML platform through efficient resource allocation and infrastructure management.

Collaborate with IT and cloud operations teams to ensure seamless integration and smooth operation of the AI/ML platform.

Monitor and analyze platform performance, identify bottlenecks, and implement necessary improvements to enhance efficiency and scalability.

Oversee the development and deployment of high-quality and impactful AI/ML models across various domains, such as content recommendation, personalization, content creation, and fraud detection.

Ensure the quality, accuracy, and fairness of AI/ML models through rigorous testing, validation, and monitoring.

Develop and implement MLOps best practices, including CI/CD pipelines, automated testing, and model monitoring, to streamline the model development and deployment process.

Collaborate with data scientists and engineers to ensure efficient and effective model training, deployment, and maintenance.

Drive the adoption of AI/ML models across the organization through clear communication, training, and support.

Lead and mentor a high-performing team of AI/ML engineers and architects.

Foster a collaborative and innovative team culture that encourages experimentation, learning, and growth.

Recruit, hire, and onboard top talent in the field of AI/ML.

Provide guidance and support to team members on technical challenges and career development.

Track team performance, identify areas for improvement, and implement necessary changes to enhance team effectiveness.

Ensure all AI/ML initiatives adhere to regulatory requirements, ethical guidelines, and company policies.

Define processes for monitoring, auditing, and improving AI models in production.

Advocate for responsible AI practices within the organization.

Master’s or Ph.D. degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical field from a recognized university.

Specialized certifications or training in AI, Machine Learning, Deep Learning, or similar areas are a plus.

12+ years of experience in AI/ML technologies, with at least 8+ years in a leadership role overseeing large-scale AI/ML projects and teams.

Proven experience in leading AI/ML architecture design, deployment, and optimization in enterprise-scale environments, preferably within a Media & Entertainment or similar high-tech industry.

Strong track record of implementing cloud-based AI solutions (AWS, Azure, GCP) and experience with AI/ML frameworks (TensorFlow, PyTorch, Keras, etc.).

Extensive experience in building, scaling, and maintaining AI platforms, machine learning models, and data architectures.

Expertise in integrating AI/ML technologies with business processes, including content management, user analytics, and personalized recommendations.

Expertise in AI/ML model development, architecture design, and advanced analytics.

Deep understanding of cloud-native AI technologies, big data systems, and distributed computing.

Experience with AI model deployment pipelines, continuous integration, and delivery (CI/CD).

Proficiency in multiple programming languages (Python, Java, C++, etc.) and machine learning libraries.

In-depth knowledge of data engineering, data pipelines, and data lake architecture.

Exceptional leadership and people management skills, with experience managing cross-functional teams.

Strong communication skills, with the ability to convey complex technical concepts to business leaders and stakeholders.

Deep understanding of AI ethics, privacy, and governance principles.

Strong problem-solving abilities, with a passion for innovation and creativity.

Proven ability to collaborate effectively across departments and lead change in a complex, fast-paced environment.