JPMorgan Software Engineer II - AI/ML 

India, Karnataka, Bengaluru 

574061587

Job responsibilities

• Design and implement highly scalable and reliable data processing pipelines and deploy model inference services.
• Deploy solutions into public cloud (AWS or Azure) infrastructure.
• Experiment, develop and productionize high quality machine learning models, services, and platforms to make a huge technology and business impact.
• Write code to create several machine learning experimentation pipelines.
• Design and implement feature engineering pipelines and push them to feature stores.
• Analyze large datasets to extract actionable insights and drive data-driven decision-making.
• Ensure the scalability and reliability of AI/ML solutions in a production environment.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 2+ years applied experience
• Proficiency in programming languages such as Python, Java etc.
• Proficiency in writing comprehensive test cases, with a strong emphasis on using testing frameworks such as pytest to ensure code quality and reliability.
• Full-stack experience, including JavaScript frameworks such as React, would be highly valuable
• Expert knowledge of one of the cloud computing platforms: Amazon Web Services (AWS), Azure, Kubernetes.
• Experience in using GenAI (OpenAI or other models Amazon Bedrock) to solve business problem.
• Experience building data pipelines for both structured and unstructured data processing.
• Experience in developing APIs and integrating NLP or LLM models into software applications
• Hands-on experience with cloud platforms (AWS or Azure) for AI/ML deployment and data processing.
• Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics.
• Excellent communication skills and ability to communicate with senior technical and business partners

Preferred qualifications, capabilities, and skills

• Expert in at least one of the following areas: Natural Language Processing, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis.
• Knowledge of machine learning frameworks: Pytorch, Keras, MXNet, Scikit-Learn, as well as LLM frameworks, such as LangChain, LangGraph, etc
• Understanding of finance or investment banking businesses is an added advantage