Job Title:  Technology & Transformation- Engineering- AI & Data- AI Architect - Manager

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The team

Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning.     

Job Description:

• Data Handling & Feature Engineering: 

Collect, preprocess, and analyse payment datasets (credit card, UPI) to extract meaningful features, including embeddings, time-series signals, and customer behavior patterns. 

• ML Model Development: 

Design and implement models for fraud detection, customer segmentation, and demand forecasting using tools like TensorFlow, PyTorch, and Scikit-learn. 

• Generative AI & Foundation Models: 

Apply and fine-tune OSS LLMs (e.g., Hugging Face Transformers, Llama, GPT-J, Falcon) for use cases such as: 

• • Synthetic data generation 
  • Transaction summarization 
  • Conversational AI for payment-related queries 

Key skills required: 

• Model Evaluation & Optimization: 
• Use metrics like AUC-ROC, precision, recall, and F1-score to evaluate models. Apply hyperparameter tuning and distributed training for performance improvement. 
• Deployment & MLOps: 
• Deploy ML/GenAI models using tools like MLflow, Kubeflow, SageMaker, and Docker/Kubernetes. Set up real-time inference pipelines and monitor model drift and reliability in production. 
• Collaboration & Communication: 
• Work with cross-functional teams (data scientists, engineers, product) to define requirements and deliver business-impacting solutions. Present findings to both technical and non-technical stakeholders. 
• 7 to 10 Years of proven experience as a Machine Learning Engineer, Data Scientist.
• Strong knowledge of machine learning, statistics, and data science concepts and techniques. 
• Proficient in programming languages such as Python, R, and Java. 
• Experience with data processing tools like SQL, Spark, and Hadoop. 
• Proficient in using frameworks like TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers, and other OSS LLMs. 
• Hands-on experience with foundational models, such as BERT, GPT, T5, and Vision Transformers (ViT). 
• Experience with credit card and UPI payment data use cases (e.g., fraud detection, transaction risk assessment, customer analytics) is a plus. 
• Experience fine-tuning and deploying OSS LLMs for specific tasks such as text summarization, synthetic data generation, and NLP applications in payments. 
• Familiarity with frameworks/tools like Hugging Face, LangChain, and LlamaIndex. 
• Hands-on experience deploying ML and GenAI models in production environments with tools like MLflow, Kubeflow, Docker, and Kubernetes. 
• Excellent communication and presentation skills, with the ability to explain complex concepts 

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

Location and Way of Working: 

• Base location: Banglore