AI/ML Lead

We are seeking a highly experienced and results-driven AI/ML Team Lead to drive the development, execution, and delivery of Artificial Intelligence and Machine Learning solutions across multiple business functions and projects. The successful candidate will be responsible for leading a team of AI/ML Engineers, Data Scientists, MLOps Engineers, and AI Developers while ensuring the successful execution of strategic AI initiatives.

The role requires a combination of strong technical expertise, people leadership, project management, stakeholder engagement, and business acumen. The AI/ML Team Lead will play a key role in defining the organization's AI roadmap, implementing best practices, driving innovation, and ensuring the delivery of scalable, secure, and production-ready AI solutions.

This position is ideal for someone who thrives in a fast-paced environment, enjoys solving complex business problems through AI, and has a proven track record of managing multiple projects and technical teams simultaneously.

AI Strategy & Leadership

• Define and execute the organization's AI and Machine Learning strategy aligned with business goals.
  
• Lead AI transformation initiatives and identify opportunities where AI can create measurable business value.
  
• Collaborate with executive leadership to develop long-term AI roadmaps and innovation strategies.
  
• Establish technical governance, standards, frameworks, and best practices for AI development.
  
• Promote a culture of innovation, experimentation, knowledge sharing, and continuous improvement within the AI team.
  
• Stay updated with emerging technologies, industry trends, research advancements, and best practices in AI, ML, GenAI, and Data Science.
  

Team Leadership & People Management

• Lead, mentor, coach, and develop a team of AI Engineers, Machine Learning Engineers, Data Scientists, Prompt Engineers, and MLOps professionals.
  
• Manage team performance through regular feedback, performance reviews, and career development planning.
  
• Foster a collaborative and high-performing team culture.
  
• Support hiring, onboarding, and retention of top AI talent.
  
• Conduct technical mentoring sessions and encourage continuous learning through certifications, workshops, and research activities.
  
• Allocate resources effectively across multiple projects and business priorities.
  

Multi-Project Management & Delivery Oversight

• Manage and oversee multiple AI/ML projects simultaneously from concept to deployment.
  
• Establish project goals, deliverables, milestones, timelines, and success metrics.
  
• Ensure projects are delivered on time, within scope, and aligned with business expectations.
  
• Monitor project progress, identify risks, and implement mitigation strategies.
  
• Prioritize tasks and manage competing business priorities effectively.
  
• Coordinate project execution across Data Engineering, Software Engineering, Product, QA, and Business teams.
  
• Provide regular status updates and executive reports to senior stakeholders.
  

AI/ML Solution Architecture & Development

• Lead the design and implementation of scalable AI/ML systems and architectures.
  

• Review and approve technical designs, model architectures, and deployment strategies.
  

• Guide teams in developing solutions involving:
  

  • Machine Learning
    
  • Deep Learning
    
  • Natural Language Processing (NLP)
    
  • Computer Vision
    
  • Generative AI
    
  • Large Language Models (LLMs)
    
  • AI Agents
    
  • Recommendation Systems
    
  • Predictive Analytics
    
  • Intelligent Automation
    

• Ensure solutions are scalable, secure, maintainable, and production-ready.
  

• Establish best practices for model training, testing, validation, deployment, and monitoring.
  

Generative AI & Large Language Models

• Lead enterprise adoption of Generative AI solutions and LLM-powered applications.
  

• Design and oversee implementation of:
  

  • RAG (Retrieval-Augmented Generation)
    
  • AI Assistants
    
  • Chatbots
    
  • Multi-Agent Systems
    
  • Knowledge Management Platforms
    
  • Intelligent Document Processing Solutions
    

• Evaluate and optimize foundation models including OpenAI, Azure OpenAI, Claude, Gemini, Llama, and other leading AI technologies.
  

• Implement prompt engineering and model optimization strategies.
  

• Develop AI governance frameworks for responsible AI implementation.
  

MLOps & Production Deployment

• Establish MLOps frameworks and best practices.
  
• Design CI/CD pipelines for AI model deployment and monitoring.
  
• Implement automated model retraining, performance tracking, and monitoring processes.
  
• Ensure proper version control for datasets, models, and experiments.
  
• Lead deployment of AI applications across cloud and on-premise infrastructure.
  
• Manage model lifecycle management and continuous improvement initiatives.
  

Stakeholder & Business Collaboration

• Work closely with business leaders to understand strategic objectives and identify AI opportunities.
  
• Translate business requirements into AI solutions and technical roadmaps.
  
• Communicate technical concepts effectively to both technical and non-technical stakeholders.
  
• Present project progress, ROI, and business impact to senior management and executives.
  
• Serve as the primary point of contact for AI initiatives across the organization.
  

Data Strategy & Governance

• Collaborate with Data Engineering teams to ensure data quality, availability, and accessibility.
  
• Establish data governance, security, privacy, and compliance standards.
  
• Ensure responsible handling of sensitive and confidential information.
  

Research & Innovation

• Drive innovation through research, experimentation, and proof-of-concept development.
  
• Evaluate new AI frameworks, tools, and emerging technologies.
  
• Establish AI Centers of Excellence and knowledge-sharing programs.
  
• Encourage participation in AI communities, conferences, and research initiatives.
  

Education

• Bachelor's or Master's degree in:
  • Computer Science
    
  • Artificial Intelligence
    
  • Machine Learning
    
  • Data Science
    
  • Software Engineering
    
  • Related Technical Field

Experience

• 7+ years of experience in AI/ML, Data Science, or Advanced Analytics.
  
• Minimum 3+ years of experience leading AI/ML teams.
  
• Proven experience managing multiple AI projects simultaneously.
  
• Hands-on experience delivering enterprise-scale AI solutions.
  
• Experience working with cross-functional teams and senior stakeholders