AI Practice Lead

Summary

Join MAS Global as their AI Practice Lead and spearhead their AI initiatives. Lead and mentor high-performing AI teams, architecting and delivering cutting-edge AI solutions. Drive the adoption of advanced AI technologies and build a thriving internal and external AI community. Oversee the entire AI project lifecycle, from design and development to deployment and optimization. This role requires strong technical leadership, excellent communication skills, and a passion for AI innovation. You will also be responsible for building an AI Center of Excellence and fostering a culture of knowledge sharing.

Requirements

• 10+ years of hands-on experience in AI, machine learning, and data science, with at least 4+ years leading AI teams and implementing AI-driven solutions in production
• Deep technical knowledge of AI methodologies and tools, including experience with machine learning algorithms, neural networks, NLP, computer vision, reinforcement learning, and generative models
• Strong proficiency in AI frameworks such as TensorFlow, PyTorch, and Keras, and familiarity with cloud platforms like AWS, GCP, or Azure for deploying AI solutions
• Expertise in AI model lifecycle management, including model training, tuning, and deployment pipelines (e.g., MLOps, CI/CD)
• Demonstrated experience in managing and developing technical talent, with a focus on mentoring AI engineers and creating high-performing teams
• Proven experience in leading technical solutioning, client engagements, and the design and delivery of AI solutions that solve real-world business problems
• Strong communication skills, with the ability to convey complex AI concepts to both technical and non-technical audiences
• Ability to drive thought leadership, contribute to open-source projects, and engage in AI research and development communities
• Bilingual in English (Spanish proficiency is a plus)

Responsibilities

• Design and Build Scalable AI Architectures: Lead the design and implementation of scalable, high-performance AI architectures, utilizing technologies like deep learning, reinforcement learning, natural language processing (NLP), and generative AI. Focus on data pipelines, model deployment, and performance optimization
• Advanced AI Technologies: Drive the adoption of emerging AI technologies, including but not limited to, TensorFlow, PyTorch, Kubernetes for AI, and cloud-native AI frameworks on AWS, Azure, or Google Cloud
• End-to-End AI Project Delivery: Oversee the complete lifecycle of AI projects, from solution design, prototyping, and POCs to deployment and optimization. Ensure alignment between business needs and technical execution, while maintaining high-quality standards throughout the project lifecycle
• AI Model Management: Lead the development, training, and fine-tuning of machine learning models, particularly deep neural networks, large language models (LLMs), and computer vision models. Implement robust model monitoring and lifecycle management strategies for production systems
• Technical Hands-On Leadership: Provide direct technical guidance to AI engineers in areas such as data preprocessing, model training, hyperparameter tuning, and performance evaluation. Ensure that teams are using the most effective techniques and tools for AI development
• AI Security and Ethical Considerations: Ensure that AI solutions are built with a focus on security, fairness, and ethics. Advocate for responsible AI practices, including bias mitigation, explainability, and data privacy concerns
• Mentorship and Talent Development: Lead, mentor, and develop a high-performing AI team by providing continuous learning opportunities, fostering a culture of innovation, and supporting career growth. Provide technical guidance on complex problems while ensuring that team members have the support they need to succeed
• AI Talent Acquisition: Work closely with the HR and recruitment teams to hire top-tier AI talent, ensuring that candidates have the right technical skills and fit within MAS Global's culture of innovation
• Building an AI Center of Excellence (CoE): Lead the formation of an internal AI Center of Excellence, creating frameworks, standards, and best practices for AI development, deployment, and maintenance across MAS Global
• Team Collaboration: Foster an environment of collaboration across multidisciplinary teams, including data scientists, machine learning engineers, software engineers, and product managers. Ensure clear communication between technical and non-technical teams
• Internal Education and Training: Spearhead the development of AI-focused training programs and workshops aimed at upskilling MAS Global’s technical teams. This could include advanced training on specific AI technologies, ML frameworks, and AI ethics
• MAS Academy and Knowledge Sharing: Design and deliver specialized AI courses within MAS Academy to promote continuous learning across the organization. Foster a culture of knowledge-sharing through regular internal seminars, tech talks, and collaborative learning sessions
• AI Community Building: Organize and lead both internal and external AI events, webinars, and hackathons to encourage collaboration, knowledge exchange, and innovation. Establish MAS Global as a recognized thought leader in the AI space by presenting at major industry conferences, contributing to AI publications, and actively engaging with academic institutions and research communities
• Collaborations and Partnerships: Build relationships with external AI research organizations, universities, and AI thought leaders to bring new ideas and research into MAS Global’s practice
• AI Solution Design for Clients: Engage with clients to design and deliver AI-driven solutions that solve complex business problems. Lead technical discovery sessions, develop AI roadmaps, and propose scalable architectures that leverage cutting-edge AI technologies
• AI Solution Integration: Ensure smooth integration of AI solutions with existing enterprise systems and data infrastructure. Work with teams to deploy AI models into production environments, considering factors like scalability, latency, and real-time processing needs
• Proof of Concept (PoC) Leadership: Lead the development of PoCs and prototypes that demonstrate the value of AI solutions to clients. Oversee testing and iteration, ensuring that PoCs are scalable and production-ready
• AI Solution Feasibility and Delivery: Collaborate with sales teams and client stakeholders to define the scope and technical feasibility of AI solutions, ensuring that proposed architectures can be executed within client timelines and budgets
• Internal AI Community Engagement: Foster a community of practice within MAS Global by organizing regular technical forums, brown bag sessions, and AI roundtables. Encourage employees to contribute ideas, experiments, and new AI tools or techniques
• External AI Advocacy: Position MAS Global as a leader in the AI space through active engagement in external AI communities. Speak at conferences, contribute to open-source AI projects, and publish articles and white papers on innovative AI topics
• AI Competitions and Hackathons: Organize and sponsor AI-related competitions and hackathons to identify talent, promote creative solutions to AI challenges, and engage with the broader AI community
• Cross-Department Collaboration: Work closely with product managers, sales, and delivery teams to ensure alignment on AI project goals, timelines, and client expectations
• Reporting and Metrics: Regularly report on the progress of AI initiatives, tracking key metrics such as project completion, team performance, model accuracy, and client satisfaction. Use data to drive decisions and improve future AI strategies

Preferred Qualifications

• Passionate about AI innovation, with a drive to stay ahead of technological trends and an eagerness to share knowledge with others
• Strong technical leader who thrives in a fast-paced environment and enjoys mentoring and empowering teams
• Strategic thinker with a collaborative mindset and an ability to connect technical solutions to broader business objectives
• Highly organized, with the ability to balance technical depth with a focus on business impact
• Entrepreneurial and results-driven, with a clear focus on delivering successful AI solutions for clients and MAS Global