Data Science Engineer, VP

7 hours ago

Electronic City, India Deutsche Bank Full time

Description

We are seeking a seasoned Data Science Engineer to spearhead the development of intelligent, autonomous AI systems. The ideal candidate will have a robust background in agentic AI, LLMs, SLMs, vector DB, and knowledge graphs. This role involves designing and deploying AI solutions that leverage Retrieval-Augmented Generation (RAG), multi-agent frameworks, and hybrid search techniques to enhance enterprise applications.

What we’ll offer you

As part of our flexible scheme, here are just some of the benefits that you’ll enjoy

Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Complementary Health screening for 35 yrs. and above

Your key responsibilities

Design & Develop Agentic AI Applications: Utilise frameworks like LangChain, CrewAI, and AutoGen to build autonomous agents capable of complex task execution. Implement RAG Pipelines: Integrate LLMs with vector databases (e.g., Milvus, FAISS) and knowledge graphs (e.g., Neo4j) to create dynamic, context-aware retrieval systems. Fine-Tune Language Models: Customise LLMs (e.g., Gemini, chatgpt, Llama) and SLMs (e.g., Spacy, NLTK) using domain-specific data to improve performance and relevance in specialised applications. NER Models: Train OCR and NLP leveraged models to parse domain-specific details from documents (e.g., DocAI, Azure AI DIS, AWS IDP) Develop Knowledge Graphs: Construct and manage knowledge graphs to represent and query complex relationships within data, enhancing AI interpretability and reasoning. Collaborate Cross-Functionally: Work with data engineers, ML researchers, and product teams to align AI solutions with business objectives and technical requirements. Optimise AI Workflows: Employ MLOps practices to ensure scalable, maintainable, and efficient AI model deployment and monitoring.

Your skills and experience

13+ years of professional experience in AI/ML development, with a focus on agentic AI systems. Proficient in Python, Python API frameworks, SQL and familiar with AI/ML frameworks such as TensorFlow or PyTorch. Experience in deploying AI models on cloud platforms (e.g., GCP, AWS). Experience with LLMs (e.g., GPT-4), SLMs (Spacy), and prompt engineering. Understanding of semantic technologies, ontologies, and RDF/SPARQL. Familiarity with MLOps tools and practices for continuous integration and deployment. Skilled in building and querying knowledge graphs using tools like Neo4j. Hands-on experience with vector databases and embedding techniques. Familiarity with RAG architectures and hybrid search methodologies. Experience in developing AI solutions for specific industries such as healthcare, finance, or e-commerce. Strong problem-solving abilities and analytical thinking. Excellent communication skills for cross-functional collaboration. Ability to work independently and manage multiple projects simultaneously.

How we’ll support you

Training and development to help you excel in your career Coaching and support from experts in your team A culture of continuous learning to aid progression A range of flexible benefits that you can tailor to suit your needs

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