JPMorgan Applied AI ML Associate Sr 

India, Karnataka, Bengaluru 

316760917

Job Responsibilities

• Build and train production grade ML models on large-scale datasets to solve various business use cases for Commercial Banking.
• Use Deep Learning frameworks like CNN, RNN, LSTM and Attention for solving use cases requiring semantic search, named entity resolution, forecasting, anomaly detection among many other techniques.
• Explore LLM models and evaluate model performance and accuracy. Improve the accuracy of the models by customizing for specific use cases by using tools like Langchain, Few shot learning, Chain of thought and other prompt engineering techniques.
• Implement Retrieval-Augmented Generation (RAG) methods to enhance the LLM's ability to retrieve and generate accurate answers from large datasets. Develop end-to-end ML pipelines necessary to transform existing applications and business processes into true AI systems.
• Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to define requirements and deliver high-quality solutions.
• You will collaborate to develop large-scale data modeling experiments, evaluating against strong baselines, and extracting key statistical insights and/or cause and effect relations.
• Utilize Prompt Engineering techniques to fine-tune and optimize LLMs for specific use cases and improve response accuracy and relevance.

Required qualifications, capabilities, and skills

• Advanced Degree in field of Computer Science, Data Science or equivalent discipline
• Experience as a hands-on Data Scientist/ ML Engineer
• Strong communication skills along with significant experience of managing stakeholder of diverse background
• Hands on expertise with Python, PySpark, DL frameworks like TensorFlow/PyTorch over GPU is preferred, BERT, SBERT,etc
• Experience in designing and building highly scalable distributed ML models in production
• Experience with analytics (ex: SQL, Python, AWS suite, Spark)
• Experience with machine learning techniques and advanced analytics (e.g. regression, classification, clustering, time series, econometrics, causal inference, mathematical optimization)

Preferred qualifications, capabilities, and skills

• Experience, as a Data Science lead, in driving projects end to end is preferred
• Experience in LLM, building RAG pipeline is preferred
• Experience in large scale Machine Learning system design is preferred
• Experience working with end-to-end pipelines consisting of Cloud services is preferred, preferably, with AWS ML ecosystem (i.e. SageMaker, etc.)