VP of Applied AI (The Innovation Executor) at Unreal Gigs

Are you passionate about bringing cutting-edge AI research into practical applications that drive real-world impact? Do you have the strategic acumen and technical expertise to lead a team in transforming innovative AI models into scalable products that revolutionize industries? If you’re ready to bridge the gap between research and product development, our client has the perfect role for you. We’re seeking a VP of Applied AI (aka The Innovation Executor) to drive AI initiatives from concept to production, ensuring our client’s products and services leverage AI advancements for a competitive edge.

As the VP of Applied AI at our client, you’ll lead a talented team of applied scientists, machine learning engineers, and data scientists. You’ll work closely with product, engineering, and business teams to apply AI models to diverse applications, from customer personalization to predictive analytics. Your work will be essential in shaping the company’s AI roadmap and delivering solutions that enhance user experiences, optimize processes, and unlock new revenue streams.

Key Responsibilities:

1. Set the Strategic Vision for Applied AI: Develop a strategic vision and roadmap for applied AI that aligns with business objectives and maximizes impact. You’ll prioritize projects that translate research into practical applications, from recommendation systems to automation tools.
2. Lead the Development and Deployment of AI-Powered Products: Oversee the end-to-end lifecycle of AI applications, including model development, validation, and deployment. You’ll ensure that applied AI projects integrate seamlessly with products, meeting scalability, reliability, and performance requirements.
3. Collaborate with Cross-Functional Teams to Drive Innovation: Partner with product, engineering, and business leaders to identify AI opportunities across business units. You’ll ensure that applied AI solutions align with product strategies and provide measurable value to users and stakeholders.
4. Build and Lead a High-Performing Applied AI Team: Recruit, mentor, and manage a team of applied scientists, data scientists, and engineers. You’ll foster a collaborative culture focused on innovation, experimentation, and the continuous improvement of AI-powered solutions.
5. Ensure AI Model Robustness and Ethical Use: Establish best practices for model evaluation, ensuring robustness, fairness, and interpretability. You’ll set guidelines for responsible AI use, balancing innovation with ethical considerations to uphold trust and transparency.
6. Drive Continuous Improvement and Optimization: Leverage data-driven insights to continually optimize AI models in production. You’ll implement monitoring and feedback loops to ensure AI applications remain relevant, accurate, and aligned with evolving user needs.
7. Stay Updated on AI Trends and Technological Advancements: Keep abreast of the latest developments in applied AI, from algorithmic advancements to industry best practices. You’ll ensure that the company remains competitive and that applied AI solutions incorporate cutting-edge technologies.

Required Skills:

• Applied AI and Machine Learning Expertise: Extensive experience with applied AI, including model development, deployment, and production scaling. You’re skilled in transforming research into AI-driven applications that solve real-world problems.
• Strategic Vision and Business Acumen: Proven ability to set a strategic vision for applied AI initiatives and align them with organizational goals. You understand market trends and can identify AI opportunities that drive growth and differentiation.
• Leadership and Team Development: Strong leadership skills with experience building and managing high-performing AI teams. You’re adept at inspiring talent, fostering innovation, and ensuring teams deliver results.
• Product and Engineering Collaboration: Experience working closely with product and engineering teams to integrate AI models into scalable products. You know how to ensure applied AI solutions meet technical and business requirements.
• Ethics and Responsible AI Practices: Knowledge of responsible AI practices, including model fairness, bias mitigation, and transparency. You’re committed to developing AI that serves users ethically and builds trust.

Educational Requirements:

• Master’s or Ph.D. in Computer Science, Artificial Intelligence, Data Science, or a related field. Equivalent experience with a strong background in applied AI may be considered.
• Certifications in data science, machine learning engineering, or AI product management are advantageous.

Experience Requirements:

• 10+ years of experience in applied AI, machine learning, or a similar field, with a strong track record of implementing AI solutions in business contexts.
• 5+ years of experience in a leadership role, directing teams in AI or product-focused environments.
• Experience in deploying large-scale AI models and integrating them into products is highly desirable.