Data and AI Engineer

About MBRDI\:

Mercedes-Benz Research and Development India (MBRDI), headquartered in Bengaluru with a satellite office in Pune, is the largest R&D center for Mercedes-Benz Group AG outside of Germany. Our mission is to drive innovation and excellence in automotive engineering, digitalization, and sustainable mobility solutions, shaping the future of mobility.

We are seeking a motivated and curious AI Engineer with a strong interest in Generative AI (GenAI) and Data Science to join our Applied AI team. In this role, you will contribute to the development and deployment of cutting-edge AI solutions leveraging Large Language Models (LLMs) and other GenAI technologies. This is an excellent opportunity for early-career professionals to gain hands-on experience in applying AI to real-world challenges across business and technical domains.

Key Responsibilities

• Model Development & Experimentation
  • Work on training, fine-tuning, and evaluating generative AI models (LLMs, diffusion models, multimodal systems).
  • Experiment with prompt engineering, RAG (Retrieval-Augmented Generation), and agent-based architectures.
  • Benchmark model performance and optimize for accuracy, efficiency, and scalability.
• Prototyping & Deployment
  • Build proof-of-concept applications showcasing GenAI capabilities for business use cases.
  • Support integration of GenAI models into enterprise workflows, APIs, or platforms.
  • Collaborate with MLOps engineers to ensure models are production-ready.
• Research & Innovation
  • Stay updated with the latest advancements in GenAI, NLP, and multimodal AI.
  • Explore new architectures, frameworks, and evaluation methods.
  • Contribute to knowledge sharing within the team and broader organization.
• Collaboration & Stakeholder Engagement
  • Work closely with cross-functional teams (product, engineering, business) to understand problem statements and co-create solutions.
  • Translate research findings into actionable insights for business applications.
  • Present results and demos to both technical and non-technical stakeholders.

Key Responsibilities

• Model Development & Experimentation
  • Work on training, fine-tuning, and evaluating generative AI models (LLMs, diffusion models, multimodal systems).
  • Experiment with prompt engineering, RAG (Retrieval-Augmented Generation), and agent-based architectures.
  • Benchmark model performance and optimize for accuracy, efficiency, and scalability.
• Prototyping & Deployment
  • Build proof-of-concept applications showcasing GenAI capabilities for business use cases.
  • Support integration of GenAI models into enterprise workflows, APIs, or platforms.
  • Collaborate with MLOps engineers to ensure models are production-ready.
• Research & Innovation
  • Stay updated with the latest advancements in GenAI, NLP, and multimodal AI.
  • Explore new architectures, frameworks, and evaluation methods.
  • Contribute to knowledge sharing within the team and broader organization.

• Collaboration & Stakeholder Engagement

  • Work closely with cross-functional teams (product, engineering, business) to understand problem statements and co-create solutions.
  • Translate research findings into actionable insights for business applications.
  • Present results and demos to both technical and non-technical stakeholders.