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JPMorgan ML Scientist- VP United Kingdom, England, London 707029235
Yesterday
As a Lead Machine Learning Scientist at JPMorgan Chase within the International Consumer Bank, you will be a part of a flat-structure organization. Your responsibilities are to deliver end-to-end cutting-edge solutions in the form of cloud-native microservices architecture applications leveraging the latest technologies and the best industry practices. You are expected to be involved in the design and architecture of the solutions while also focusing on the entire SDLC lifecycle stages.
Job spec customisation requirements:
- Job responsibilities :
- Lead the development and maintenance of machine learning models to solve complex business problems
- Develop the technical skills of junior colleagues through mentorship and training
- Collaborate with cross functional teams to identify opportunities for leveraging data to drive business solutions
- Analyse large, heterogenous datasets to extract actionable insights and inform decision-making
- Stay updated with the latest advancements in machine learning and especially Large Language Models and agentic systems
- Identify the right state of the art solutions for the bank’s objectives and manage colleagues to implement them as clean, production-ready code
- Communicate findings and recommendations through clear and concise reports and presentations
- Required qualifications, capabilities and skills
- Experience leading teams to deliver production machine learning solutions
- Proficiency in Python and SQL and familiarity with good software engineering practices
- Excellent written and verbal communication
- Strong experience developing, testing machine learning solutions using frameworks such as TensorFlow, PyTorch or scikit-learn
- Solid intuitive grasp offundamentalconcepts from probability, statistics, linear algebra and calculus
- Collaborative, humble and enthusiastic attitude
- Preferred qualifications, capabilities and skills
- Experience deploying on AWS cloud infrastructure using Lambda, Glue, S3 etc
- Experience in deep neural networks and familiarity with the latest developments in related fields
- Experience in LLM model finetuning and continuous learning techniques
- Experience in prompt engineering techniques and state-of-the-art LLM architectures
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