SLM Data Science Lead - Architect AI/ML

Position Title: SLM Data Science Lead - Architect AI/ML Department: Engineering & Technology Function: AI/ML Platform Engineering Role Summary The Principal Data Scientist / SLM Model Development Architect is a senior technical leadership role responsible for defining the architecture, strategy, and enterprise adoption of Small Language Models (SLMs) and advanced AI solutions. This role provides end-to-end ownership of model design, optimization, deployment, and governance while mentoring teams and influencing AI strategy across the organization. Responsibilities Architecture & Strategy Define and own the enterprise architecture, standards, and roadmap for Small Language Model (SLM) development.Design domain-specific SLMs optimized for accuracy, latency, cost, and scalability.Drive architectural decisions for model selection, fine-tuning, compression, and inference optimization.Ensure alignment of AI solutions with enterprise security, compliance, and governance requirements. Advanced Model Development Lead the design, development, and deployment of ML, DL, and SLM-based solutions.Apply deep mathematical and statistical knowledge to optimize model performance.Demonstrate successful delivery of multiple production deployments with measurable business impact.Provide architectural oversight for traditional ML, deep learning, and NLP-based systems.NLP & Language Modeling Architect and guide solutions involving NLP, embeddings, transformers, and language models.Lead fine-tuning and adaptation of language models for domain-specific use cases.Establish best practices for prompt engineering, evaluation metrics, and performance monitoring.Technical & Platform Leadership Provide technical authority in Python, scientific computing, and data processing frameworks.Guide teams on the effective use of TensorFlow, PyTorch, and Keras.Ensure high-quality analytical data access through complex and optimized SQL designs.Oversee development in Linux and GPU-based environments.Cloud, MLOps & Production Readiness Architect and govern ML/AI solutions on AWS or Azure platforms.Define and enforce MLOps standards, including CI/CD, model versioning, monitoring, and lifecycle management.Ensure reliability, scalability, and maintainability of AI systems in production.Leadership & Mentorship Act as Principal Architect and technical mentor for Data Scientists and ML Engineers.Lead design reviews, technical decision forums, and architectural governance boards.Collaborate closely with product, engineering, security, and compliance stakeholders.Drive innovation while ensuring delivery discipline in Agile environments. Required Skills & Expertise Strong foundation in ML algorithms: Random Forest, SVM, Regression models, Boosting & BaggingDeep learning expertise: CNN, RNN, LSTM, GRUAdvanced NLP and language model experienceExpert-level Python programmingCloud-based ML architecture and deploymentEnterprise AI governance and best practices Preferred / Nice to Have Experience with Computer Vision casesExposure to Responsible AI, model risk management, and regulatory complianceExperience defining AI strategy at an organizational or platform level Role Level Principal / ArchitectIndividual Contributor with enterprise-level technical leadership responsibilities Experience 8 - 12 years of experience in Data Science, Machine Learning, and Deep LearningProven experience in architecting and deploying production-grade AI/ML systems at enterprise scale Educational Qualification ME / BE / MCA / PhDPhD preferred for advanced research and architectural leadership roles .