Senior AI & Generative AI Specialist

About the job

Company Description The Bosch Group is a leading global supplier of technology and services, in the areas of Automotive Technology, Industrial Technology, Consumer Goods, Energy and Building Technology. In India, the Group operates through nine companies with a combined strength of over 30,000 associates which includes around 14,000 research and development associates. Job Description Role Summary We are seeking a Senior AI & Generative AI Specialist to architect, build, and scale production-grade AI and GenAI solutions. The role demands deep hands-on expertise, strong system architecture skills, and the ability to lead cross-functional teams delivering result oriented & compliant AI systems. This role will own end-to-end AI lifecycle — from problem framing and model design to deployment, monitoring, governance, and business impact — with a strong emphasis on Machine learning, GenAI, LLM fine-tuning, RAG systems, and Responsible AI. Key Responsibilities AI & GenAI Architecture • Design and architect enterprise-scale AI and Generative AI systems, including LLM-based applications, RAG pipelines, fine-tuned models, and multimodal AI systems. • Lead development of AI platforms and frameworks enabling reusable, scalable AI services (AI-as-a-Service). • Define model selection strategies, fine-tuning approaches, and inference optimization. Machine Learning & Deep Learning • Develop and deploy advanced ML/DL models across: • Computer Vision (segmentation, detection, classification) • NLP (BERT, GPT, Transformers) • Generative AI (Diffusion models, GANs, multimodal systems) • Time-series forecasting, predictive analytics, anomaly detection. • Drive model optimization, hyperparameter tuning, and performance benchmarking. • Ensure model explainability, fairness, bias detection, and mitigation. GenAI & LLM Systems • Build GenAI applications & Agents including: • Intelligent document processing • Automated report generation • Smart ticketing and customer escalation systems • Knowledge assistants using RAG + vector databases • Implement prompt engineering, evaluation frameworks, and guardrails. • Optimize inference cost, latency, and scalability in cloud environments. MLOps & Production Deployment • Establish MLOps best practices: • CI/CD for ML • Model versioning and monitoring • Automated retraining pipelines. • Deploy AI services using Docker, Kubernetes, MLflow, FastAPI, Flask. Ensure high availability, low latency, and cloud cost optimization. Cloud & Big Data • Architect AI workloads on Azure, Databricks, Spark. • Build scalable data pipelines for large-scale training and inference. • Leverage distributed computing for large datasets and real-time inference. Leadership & Stakeholder Engagement • Consult and mentor AI engineering and data science teams. • Collaborate with the AI working group & international stakeholder community. • Translate business and domain problems into AI solutions with measurable impact. • Drive innovation initiatives, patents, and hackathon-level experimentation. Qualifications • Master’s degree in Data Science, AI, or related field. • Experience in AI, Agentic AI, Advance data analytics usecases in a manufacturing environment. • Strong understanding of AI governance and compliance. • >8 years of experience in buildup and delivery of AI/ML usecases with proven business benefits. • Leadership of AI/ML teams would be an added advantage.