Head of AI/ML

About Role:
We are seeking an experienced and visionary Head of AI/ML to lead our Artificial Intelligence and Machine Learning initiatives. This role combines strategic leadership, technical expertise, and stakeholder management to build innovative, scalable, and ethical AI solutions. The ideal candidate will have a proven track record of driving AI/ML strategy, managing high-performing teams, and delivering impactful solutions across diverse business domains.Collaborate with Product, Engineering, and Business leaders to drive AI-led innovation.ResponsibilitiesLead, mentor, and scale a team of data scientists, ML engineers, and research scientists.Define and execute the AI/ML strategy aligned with organizational goals.Collaborate with Product, Engineering, and Business leaders to drive AI-led innovation.Establish and enforce ethical AI practices, governance standards, and model compliance frameworks.Technical ExecutionArchitect and implement scalable ML solutions across classical ML, deep learning, and generative AI.Design, train, and deploy NLP and LLM-based models (e.g., BERT, GPT, LLaMA, T5).Build and fine-tune generative AI systems, including diffusion models and RAG-enabled pipelines.Oversee experimentation, model evaluation, performance tuning, and production deployment.Drive adoption of MLOps and LLMOps practices for efficient lifecycle management.Project & Stakeholder ManagementManage multiple AI/ML projects from research to production deployment.Translate complex business problems into technical solutions and data-driven insights.Present results, recommendations, and thought leadership to executive stakeholders.Ensure timely delivery of AI initiatives with measurable business impact.Qualifications15+ years of progressive experience in Data Science, Machine Learning, and AI.Advanced academic degree (PhD or Masters) in Computer Science, Statistics, Mathematics, or related field.Strong publication record and/or patents in AI/ML domains (preferred).Technical ExpertiseHands-on proficiency in:Classical ML: XGBoost, Random Forest, SVMDeep Learning: CNNs, RNNs, LSTMs, TransformersNLP: BERT, GPT, LLaMA, T5, etc.Generative AI: Diffusion models, LLM fine-tuning, prompt engineeringStrong programming skills in Python, SQL, and ML frameworks (scikit-learn, Hugging Face, LangChain).Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools (MLflow, Kubeflow, Airflow, Azure ML).Deep understanding of data architecture, pipelines, feature engineering, and model deployment.Familiarity with vector databases, semantic search, RAG pipelines, and GenAI safety frameworks.