Join our team as a Sr. Associate in our Applied AI ML function to advance AI in financial services and optimise business decisions.
As a Senior Associate Applied AI ML Scientist / Engineer in the Applied AI ML team at JPMorgan Commercial and Investment Bank, you'll be at the forefront of AI innovation, combining cutting-edge techniques with unique data assets to optimise business decisions and automate processes. This role offers a unique blend of scientific research and software engineering, allowing you to advance AI in financial services and build impactful products.
In this role, you will leverage the latest research in Natural Language Processing and statistical machine learning to build AI-powered products that automate processes and enhance decision-making. You will collaborate with software engineering teams to design scalable Machine Learning services and communicate AI capabilities to diverse audiences.
Job Responsibilities:
Develop and implement machine learning models and algorithms to address complex operational challenges. Design and deploy generative AI applications and agents to automate and enhance business processes. Collaborate with stakeholders to understand business needs and translate them into technical solutions. Analyse large datasets to extract actionable insights and support data-driven decision-making. Ensure the scalability and reliability of AI/ML solutions in a production environment. Stay informed about the latest advancements in AI/ML technologies and integrate them into our operations.
Required qualifications, capabilities and skills:
Advanced degree in a STEM field, with relevant experience in AI/ML. Experience in deploying AI/ML applications in a production environment, with skills in deploying models on AWS platforms such as SageMaker or Bedrock. Familiarity with MLOps practices, covering the full cycle from design, experimentation, deployment, to monitoring and maintenance of machine learning models. Expertise in machine learning frameworks such as TensorFlow, PyTorch, PyTorch Lightning, or Scikit-learn. Proficiency in Python with a strong emphasis on code quality and reliability through use of comprehensive testing. Experience with generative AI models, both as cloud service APIs (. OpenAI) and open source (. Huggingface). Experience with integrating user feedback to establish data flywheels and self-improving AI applications. Solid understanding of data preprocessing, feature engineering, and model evaluation techniques. Familiarity with cloud platforms (AWS). Excellent problem-solving skills and the ability to work independently and collaboratively. Strong communication skills to effectively convey complex technical concepts to non-technical stakeholders.
Preferred qualifications, capabilities and skills:
A . is a plus but not required Experience in the financial services industry, particularly within investment banking operations. Experience in developing AI solutions using agentic frameworks. Experience fine-tuning LLMs with advanced techniques. Experience with prompt optimisation to enhance the performance and effectiveness of prompt engineering.
