The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the adoption of advanced AI/ML technologies across the firm. Bring your expertise to take part in this exciting mission, utilizing your strong and insightful technical and people skills. We look, first and foremost, for people who are passionate about solving business problems through informed strategic vision, creative innovation, and modern ML architecture & engineering practices, leveraging our purpose-built Machine Learning platforms and/or commercial AI/ML platforms and related technologies. 

As a Machine Learning Engineer at JPMorgan Chase within the AI/ML Solution Engineering Group, you will be presented with numerous opportunities to utilize your extensive knowledge and expertise across all aspects of the machine learning lifecycle. Our work environment promotes collaboration, trust, and thought-provoking discussions, fostering diversity of thought and innovative solutions that serve the best interests of our global customers.

 

Job Responsibilities

Design and develop machine learning systems. Select appropriate datasets and data representation methods to preprocess and engineer features. Research and implement appropriate machine learning algorithms and tools. Design, implement, and support tools and workflows to facilitate machine learning experiments, tests, and production deployments. Transform and convert data science prototypes into machine learning model deployments. Develop machine learning applications according to business analytical requirements.

Required qualifications, capabilities, and skills

3+  years of applied ML engineering experience and Bachelor’s degree in computer science, information systems, or electrical engineering, or equivalent Good understanding of core algorithms, deep neural networks, and LLMs/SLMs.  Experience with NLP and the relevant frameworks and libraries. Knowledge of software development processes for machine learning systems with hands on experience with data/feature engineering, training, orchestration, model deployment/serving, model monitoring, and governance utilizing modern ML frameworks, libraries, and tools. Experience with public cloud technologies, specifically with AWS, and automation processes and tools such as IaC, and CI/CD pipelines.

Preferred qualifications, capabilities, and skills

Experience with Azure OpenAI or similar LLM APIs would be a plus. Experience with Azure would be plus Working experience with big data, data lakes/data mesh/lake house architectures, and ML data engineering processes, tools & techniques would be a plus.