Head of AI

This role is for one of the Weekday's clients

Head of AI

Data Science, Machine Learning, Artificial Intelligence, and Large Language Models (LLMs)

Requirements

Key Responsibilities

• Develop and drive the organization's end-to-end AI strategy aligned with long-term business goals and product roadmap.
• Lead, mentor, and scale a multidisciplinary team of AI/ML engineers, data scientists, and research professionals.
• Design and implement enterprise-grade Machine Learning, Deep Learning, and NLP/LLM solutions that deliver measurable business value.
• Build production-ready AI models, pipelines, experimentation platforms, and evaluation frameworks.
• Oversee the full lifecycle of model development—from problem definition, data acquisition, feature engineering, training, optimization, testing, deployment, and monitoring.
• Lead innovation around Large Language Models, generative AI, retrieval-augmented generation (RAG), fine-tuning, and prompt engineering to develop next-generation intelligent capabilities.
• Collaborate closely with engineering, product, analytics, and business leadership to identify automation opportunities and AI-driven product enhancements.
• Set standards for model governance, performance, security, scalability, and responsible AI usage.
• Stay ahead of emerging AI research, technologies, frameworks, and industry best practices to maintain competitive advantage.
• Manage budgeting, vendor relationships, partnerships, and academic or research collaborations.
• Drive a culture of continuous learning, experimentation, and excellence within the team.
  

Required Skills & Qualifications

• 7-14 years of professional experience in Data Science, AI/ML, or related disciplines, including leadership of technical teams.
• Deep expertise in supervised and unsupervised ML, deep learning architectures, statistical modeling, time-series, clustering, reinforcement learning, and AI research methodologies.
• Strong hands-on experience with LLMs and generative AI (GPT, Claude, Llama, Mistral, etc.) including fine-tuning, model alignment, RAG pipelines, embeddings, model evaluation, and vector databases.
• Proficiency in Python, ML frameworks (TensorFlow, PyTorch, JAX), and modern ML Ops pipelines and tooling.
• Strong understanding of large-scale data processing frameworks (Spark, Hadoop), SQL/NoSQL databases, cloud platforms (AWS/Azure/GCP), and containerization technologies.
• Experience building AI-enabled products end-to-end and deploying models into production environments.
• Strong analytical mindset with excellent problem-solving, leadership, communication, and stakeholder management skills.
• Proven track record of driving impact, making data-driven decisions, and working in high-growth / fast-paced environments.
• Master's or PhD preferred in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, or a related quantitative field