Machine Learning Engineer

JPMorgan Chase - Jersey City, NJ

Full-time - Mid Level

Jersey City, NJ

Credit Intermediation and Related Activities

About the position

As a Machine Learning Engineer at JPMorgan Chase within the Chief Data & Analytics Office (CDAO), you will play a crucial role in advancing the adoption of AI/ML technologies across the firm. This position involves leveraging your technical expertise to solve business problems through innovative machine learning solutions, collaborating with diverse teams to foster an environment of trust and creativity.

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.

Requirements

• 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.

Nice-to-haves

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