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Act as the technical lead responsible for implementing enterprise customers’ requirements into actionable AI/ML solutions, working in close coordination with the Enterprise AI Solution Tech Lead and Product Owners. Develop and deliver robust AI models and data pipelines (on-prem and cloud-hosted), ensuring they meet business objectives, customer expectations, and performance standards. Collaborate with the Enterprise AI team to operationalize AI use cases and translate high-level solution designs into scalable, production-ready implementations. Apply deep data science expertise to bridge the gap between AI solution design and execution, ensuring technical soundness and business relevance.
Job Responsibility:
Translate customers’ requirements into actionable data science tasks and implementation plans
Lead the development, training, and deployment of AI models and data pipelines tailored to customer-specific requirements
Ensure models and AI components are scalable, efficient, and production-ready, with smooth integration into customer systems and enterprise platforms
Serve as the subject matter expert (SME) in machine learning, data science, and AI engineering practices
Provide hands-on technical guidance to data scientists, engineers, and MLOps teams, ensuring accurate and effective implementation
Lead technical squads through virtual collaboration, guaranteeing solutions are built to meet both customer expectations and technical standards
Validate model performance, data quality, and technical fit before solution handover
Collaborate with the Enterprise Tech Leads and Product Owners to review and confirm solution readiness based on business impact, feasibility, and model validation results
Provide input on task prioritization based on complexity, risk, and technical dependencies
Work alongside the Enterprise team to ensure implemented AI solutions meet business outcomes and address real customer needs
Explain data science approaches, results, and business insights in a clear and accessible manner to both technical and non-technical stakeholders
Contribute to building customer confidence in Vodafone’s AI capabilities by ensuring reliable and transparent solution delivery
Identify technical opportunities to improve performance, accuracy, and efficiency of existing AI solutions
Recommend data science enhancements and automation strategies that can further strengthen the customer’s business outcomes
Contribute to refining reusable assets, components, and best practices for enterprise AI delivery
Requirements:
Bachelor’s or master’s degree in computer science, Data Science, Artificial Intelligence, or a related field
5–7 years of hands-on experience in developing and deploying AI/ML models in production environments
Advanced proficiency in ML libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
Strong expertise in building advanced Generative AI (GenAI) and Natural Language Processing (NLP) applications using modern large language models and frameworks (e.g., Hugging Face, Langchain, OpenAI APIs, Agents Frameworks)
Experience with big data processing and distributed computing using Apache Spark or similar technologies
Proficiency in building, deploying, and managing AI, GenAI and big data applications on cloud platforms (e.g., AWS, Azure, GCP)
Experience with MLOps tools and techniques for versioning, CI/CD, monitoring, and scaling models