Tätigkeitsbereich: Produktion Fachabteilung: Production Planning 1Gesellschaft: Mercedes-Benz Research and Development India Private Limited Standort: Mercedes-Benz Research and Development India Private Limited, Bangalore Startdatum:..7Veröffentlichungsdatum:..6Stellennummer: MERBJArbeitszeit:Vollzeit Bewerben Aufgaben

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 chance 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 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 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 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 results and demos to both technical and non-technical stakeholders.
Qualifikationen

Required Qualifications

- Bachelor’s/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, Tensor Flow, Hugging Face, Lang Chain).
- 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 (Lang Chain Agents, Llama Index, AutoGPT, etc.).
- Understanding of responsible AI practices (bias, interpretability, security).
- Contributions to open-source AI/ML projects or participation in hackathons.
Benefits Mit­arbeiter­rabatte möglich Gesund­heits­maß­nahmen Mit­arbeiter­handy möglich Essens­zulagen Betrieb­liche Alters­ver­sorgung Hybrides Arbeiten möglich Mobilitäts­angebote Mit­arbeiter Events Coaching Flexible Arbeits­zeit möglich Kinder­betreuung Park­platz Kantine, Café Gute An­bindung Barriere­frei­heit Betriebs­arzt

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📌 Data and AI Engineer (India)
🏢 Mercedes-Benz
📍 India