8 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Analyze structured and unstructured business data to generate insights for product, pricing, client experience, and sales stakeholders.
- Own end-to-end delivery of AI-powered products, including requirements, architecture, implementation, testing, deployment, monitoring, and support.
- Apply prompt engineering, RAG, fine-tuning, deep learning, and agentic AI techniques to practical business and user problems.
- Develop model services and inference systems with batching, token streaming, quantization, caching, and concurrency controls.
- Implement evaluation, red-teaming, toxicity filtering, PII handling, prompt-injection defenses, and monitoring for drift and hallucinations.
- Collaborate with product, business, operations, and data teams to translate ambiguous problems into delivered capabilities.
- Create technical documentation, architecture diagrams, and runbooks and participate in design and code reviews.
- Assess and manage operational, regulatory, reputational, and control risks in accordance with Citi policies and applicable requirements.
Requirements
- 5–8 years of relevant experience in Data Science, including Machine Learning and Deep Learning, with solid GenAI solution experience.
- At least two years of GenAI solution experience is specified within the required experience profile.
- Demonstrated experience shipping AI-enabled products to production in an agile environment.
- Hands-on experience with LLMs, transformer architectures, prompt engineering, and system prompt design.
- Experience working with structured and unstructured data from multiple sources.
- Experience with RAG, embeddings, vector indexes, chunking strategies, and retrieval evaluation.
- Experience with model customization, including fine-tuning, LoRA, PEFT, data curation, labeling, and reproducible experiment tracking.
- Experience with PyTorch or TensorFlow, the Hugging Face ecosystem, and orchestration libraries.
- Experience optimizing model serving and inference through batching, token streaming, quantization, caching, and concurrency controls.
- Experience with automatic evaluation, red-teaming, toxicity filters, PII handling, and prompt-injection defenses.
- Experience with GenAI MLOps, including feature pipelines, model registries, rollout strategies, monitoring for drift, and hallucination monitoring.
- Preferred experience includes Python and Node.js API-first services, graph databases, search infrastructure, and agentic AI solution development.
- A master’s degree in Computer Science Engineering is preferred.
Categories
About Citi
Citi is a public financial-services company offering consumer and institutional banking, credit cards, wealth management, treasury and trade solutions, and capital-markets services. It serves individuals, corporations, financial institutions, and governments in more than 160 countries and jurisdictions, earning interest and fee income from lending, payments, trading, and advisory. Founded in 1812 and headquartered in New York, it trades on the NYSE under the ticker C.