Design and develop machine learning models for BFSI use cases, implement MLOps pipelines, and build GenAI solutions while ensuring compliance and governance.
Company Description
👋🏼We're Nagarro.
We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at a scale — across all devices and digital mediums, and our people exist everywhere in the world (17500+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!
Job DescriptionREQUIREMENTS:
- 7.5+ years of hands-on experience in Machine Learning / AI Engineering.
- Proven delivery experience in BFSI, especially in GenAI solutions.
- Strong proficiency in Python, PyTorch, TensorFlow, Hugging Face.
- Deep understanding of LLM architecture, transformers, embeddings, tokenization.
- Experience with LLM fine-tuning: LoRA, PEFT, prompt tuning.
- Experience building RAG systems with Pinecone, FAISS, Weaviate, Chroma.
- Expertise in LangChain, LlamaIndex, DSPy, Semantic Kernel.
- Experience with AWS, Azure, GCP and AI services like AWS Bedrock, Azure OpenAI, Vertex AI.
- Experience with OpenSearch / ElasticSearch and vector search.
- Strong grounding in model evaluation, benchmarking, hallucination detection.
- Ability to design production-ready ML systems.
RESPONSIBILITIES:
- Design, develop, and deploy machine learning models for BFSI use cases such as credit scoring, fraud detection, churn prediction, and customer engagement.
- Build GenAI and NLP solutions using Python, PyTorch, TensorFlow, Hugging Face, and LangChain.
- Develop LLLM-based applications including fine-tuning (LoRA, PEFT, prompt tuning) and RAG pipelines using vector databases (Pinecone, FAISS, Chroma, Weaviate).
- Implement MLOps pipelines using CI/CD, MLflow, Docker, Kubernetes.
- Build scalable REST/GraphQL APIs using FastAPI, Flask, or similar frameworks.
- Design and deploy conversational AI workflows using Dialogflow, Rasa, or Microsoft Bot Framework.
- Ensure strong model governance, compliance, explainability (SHAP, LIME), and data security practices.
- Conduct model evaluation with metrics for grounding, hallucination detection, and benchmarking.
- Collaborate with business and data teams to identify AI opportunities and define success metrics.
- Optimize ML and GenAI systems for performance, scalability, and cost.
Bachelor’s or master’s degree in computer science, Information Technology, or a related field.
Top Skills
AWS
Azure
Ci/Cd
Dialogflow
Docker
Elasticsearch
Fastapi
Flask
GCP
Hugging Face
Kubernetes
Microsoft Bot Framework
Mlflow
Opensearch
Python
PyTorch
Rasa
TensorFlow
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