Data and AI Engineer

Mercedes-Benz Group AG; Bengaluru; On-site; INR 1,200,000 - 3,000,000; Full time

Job summary

Mercedes-Benz Research and Development India (MBRDI) in Bengaluru invites an AI Engineer to join the Applied AI team, focusing on Generative AI and Data Science to build cutting-edge AI solutions for real-world mobility challenges.

You will contribute to training, fine-tuning and deploying LLMs, diffusion and multimodal models, explore prompt engineering and RAG, and collaborate with cross‑functional teams to deliver enterprise-ready GenAI capabilities.

Qualifications

• Strong foundations in Machine Learning, Deep Learning, and Natural Language Processing (NLP).
• Proficiency in Python and ML/AI libraries (PyTorch, TensorFlow, Hugging Face, LangChain).
• Basic knowledge of transformer architectures and experience with pre-trained models.
• Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes) is a plus.
• Strong problem-solving, analytical, and communication skills.

Responsibilities

• Model Development & Experimentation: train, fine-tune, and evaluate GenAI models (LLMs, diffusion, multimodal).
• Prototyping & Deployment: build proofs-of-concept and integrate GenAI models into enterprise workflows.
• Research & Innovation: stay updated on GenAI, NLP, and multimodal AI; explore new architectures and evaluation methods.
• Collaboration & Stakeholder Engagement: work with product, engineering, and business teams; present findings.

Job description

Tasks

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 inGenerative AI (GenAI) and Data Scienceto 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.

Qualifications

Required Qualifications

• Bachelor’s/Master’s inComputer Science, Data Science, AI/ML, Applied Mathematics, or a related field.
• Strong foundations inMachine Learning, Deep Learning, and Natural Language Processing (NLP).
• Proficiency inPythonand relevant ML/AI libraries (PyTorch, TensorFlow, Hugging Face, LangChain).
• Basic knowledge oftransformer architecturesand experience working with pre‑trained models.
• Familiarity withcloud platforms(AWS, Azure, GCP) and containerization (Docker, Kubernetes) is a plus.
• Strong problem‑solving, analytical, and communication skills.

Preferred Skills (Good to Have)

• Experience withvector databases(Pinecone, FAISS, Weaviate) for RAG pipelines.
• Exposure toagent frameworks(LangChain Agents, LlamaIndex, AutoGPT, etc.).
• Understanding ofresponsible AI practices(bias, interpretability, security).
• Contributions to open‑source AI/ML projects or participation in hackathons.