Mercedes-Benz Bangalore Hiring Data and AI Engineer | Freshers Eligible

Tasks

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. The team aims to drive innovation and excellence in automotive engineering, digitalization, and sustainable mobility solutions.

We are looking for a motivated and curious AI Engineer with a strong interest in Generative AI (GenAI) and Data Science to join the Applied AI team. You will help develop and deploy AI solutions built on Large Language Models (LLMs) and other GenAI technologies. This is a strong opportunity for early-career professionals to gain hands-on experience applying AI to real-world business and technical problems.

Key Responsibilities

• Model Development and Experimentation: Train, fine-tune and evaluate 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 and Deployment: Build proof-of-concept applications that showcase GenAI capabilities for business use cases. Support integration of GenAI models into enterprise workflows, APIs or platforms. Work with MLOps engineers to make models production-ready.
• Research and Innovation: Keep up with the latest advances in GenAI, NLP and multimodal AI. Explore new architectures, frameworks and evaluation methods. Share knowledge within the team and the wider organization.
• Collaboration and Stakeholder Engagement: Work closely with product, engineering and business teams 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 or Master's in Computer Science, Data Science, AI/ML, Applied Mathematics or a related field.
• Strong foundations in Machine Learning, Deep Learning and Natural Language Processing (NLP).
• Proficiency in Python and relevant ML/AI libraries (PyTorch, TensorFlow, Hugging Face, LangChain).
• Basic knowledge of transformer architectures and experience working 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.

Preferred Skills (Good to Have)

• Experience with vector databases (Pinecone, FAISS, Weaviate) for RAG pipelines.
• Exposure to agent frameworks (LangChain Agents, LlamaIndex, AutoGPT, etc.).
• Understanding of responsible AI practices (bias, interpretability, security).
• Contributions to open-source AI/ML projects or participation in hackathons.