JPMorgan Applied AI ML Lead - Senior Machine Learning 

United Kingdom, England, London 

413062709

Job responsibilities

• Research and explore new machine learning methods through independent study, attending industry-leading conferences and experimentation
• Develop state-of-the art machine learning models to solve real-world problems and apply it to complex business critical problems in Cybersecurity, Software and Technology Infrastructure
• Collaborate with multiple partner teams in Cybersecurity, Software and Technology Infrastructure to deploy solutions into production
• Drive firmwide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business
• Contribute to reusable code and components that are shared internally and also ext

Required qualifications, capabilities and skills

• PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science. Or an MS with full time industry or research experience in the field.
• Hands-on experience and solid understanding of machine learning and deep learning methods
• Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
• Scientific thinking and the ability to invent
• Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
• Experience with big data and scalable model training
• Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
• Curious, hardworking and detail-oriented, and motivated by complex analytical problems
• Ability to work both independently and in highly collaborative team environments

Preferred qualifications, capabilities and skills

• Strong background in Mathematics and Statistics
• Familiarity with the financial services industries
• Experience with A/B experimentation and data/metric-driven product development
• Experience with cloud-native deployment in a large scale distributed environment
• Knowledge of large language models (LLMs) and accompanying toolsets the LLM ecosystem (e.g. Langchain, Vector databases, opensource Hugging Face Models)
• Knowledge in Reinforcement Learning or Meta Learning
• Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal
• Ability to develop and debug production-quality code
• Familiarity with continuous integration models and unit test development