Job description
This role is for one of the Weekday's clients Min Experience: 15+ years Location: Bengaluru, Karnataka, India JobType: full-time We are seeking an accomplished Head of AI to lead the vision, strategy, and execution of enterprise-scale Artificial Intelligence initiatives.
This leadership role is ideal for an experienced professional with deep expertise in Data Science & AI , Recommendation Systems , and Recommendation Engines , combined with a proven track record of building high-performing AI teams and delivering impactful machine learning solutions at scale.
As the Head of AI, you will define the organization's AI roadmap, oversee the development of intelligent products, and drive innovation by leveraging cutting-edge machine learning techniques.
You will collaborate closely with engineering, product, analytics, and business stakeholders to create AI-powered experiences that enhance customer engagement, personalization, and business growth.
Key Responsibilities Define and execute the company's long-term AI and Machine Learning strategy aligned with business objectives.
Lead the design, development, deployment, and optimization of scalable AI and machine learning solutions.
Build and enhance advanced Recommendation Systems and Recommendation Engines to deliver personalized user experiences across products and platforms.
Drive innovation in predictive analytics, personalization, ranking algorithms, and intelligent decision-making systems.
Lead and mentor multidisciplinary teams comprising Data Scientists, Machine Learning Engineers, AI Researchers, and Data Engineers.
Establish best practices for model development, validation, deployment, monitoring, and lifecycle management.
Collaborate with product, engineering, and leadership teams to identify AI opportunities and prioritize high-impact initiatives.
Develop scalable AI infrastructure and ensure seamless integration of machine learning models into production environments.
Evaluate emerging AI technologies and incorporate industry best practices to maintain technological leadership.
Ensure responsible AI practices, model governance, data privacy, fairness, and ethical AI implementation.
Present AI strategies, technical roadmaps, and business outcomes to executive leadership and key stakeholders.
Required SkillsMust-Have Skills Strong expertise in Data Science and AI Extensive experience building and optimizing Recommendation Systems Deep understanding of Recommendation Engines for large-scale applications Technical Expertise Strong knowledge of Machine Learning, Deep Learning, Reinforcement Learning, and Generative AI concepts.
Expertise in collaborative filtering, content-based recommendation, hybrid recommendation models, ranking algorithms, embeddings, and personalization techniques.
Experience with large-scale data processing and feature engineering.
Strong programming skills in Python and familiarity with modern AI/ML frameworks.
Experience with cloud platforms and distributed machine learning architectures.
Knowledge of MLOps, model monitoring, experimentation frameworks, and AI deployment pipelines.
Familiarity with data engineering, big data technologies, and scalable AI infrastructure.
Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, or a related field.
Ph.D. in a relevant discipline is an added advantage.
15–22 years of overall experience with significant leadership experience in AI, Machine Learning, or Data Science organizations.
Demonstrated success in delivering production-grade AI systems that drive measurable business impact.
Experience leading large technical teams and managing cross-functional AI initiatives.
Preferred Attributes Strategic thinker with a strong product and business mindset.
Exceptional leadership, communication, and stakeholder management skills.
Passion for innovation and applying AI to solve complex business problems.
Strong analytical and decision-making abilities with a data-driven approach.
Ability to mentor senior technical leaders while fostering a culture of continuous learning and experimentation.
Experience working in fast-paced, high-growth organizations with large-scale data ecosystems is highly desirable.
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