Machine Learning Engineer

JPMorgan Chase - Jersey City, NJ

Full-time - Mid Level

Jersey City, NJ

Credit Intermediation and Related Activities

About the position

The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is dedicated to accelerating the adoption of advanced AI/ML technologies across the firm. As a Machine Learning Engineer within the AI/ML Solution Engineering Group, you will play a crucial role in this mission, leveraging your technical expertise and interpersonal skills to solve complex business problems. We seek individuals who are passionate about utilizing modern machine learning architecture and engineering practices to drive innovation and strategic vision. Your work will involve engaging with our purpose-built Machine Learning platforms and commercial AI/ML technologies, allowing you to contribute to impactful projects that enhance our services for global customers. In this role, you will have the opportunity to engage in all aspects of the machine learning lifecycle. The environment at JPMorgan Chase promotes collaboration and trust, encouraging thought-provoking discussions that foster diversity of thought and innovative solutions. You will be responsible for designing and developing machine learning systems, selecting appropriate datasets, and implementing machine learning algorithms and tools. Your contributions will be vital in transforming data science prototypes into production-ready machine learning models, ensuring that our applications meet business analytical requirements effectively. As a Machine Learning Engineer, you will also design, implement, and support tools and workflows that facilitate machine learning experiments and production deployments. This position offers a unique chance to work with cutting-edge technologies and methodologies in a supportive and dynamic environment, where your skills and insights will be valued and utilized to their fullest potential.

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

• Bachelor's degree in computer science, information systems, or electrical engineering, or equivalent experience.
• At least 3+ years of applied ML engineering experience.
• Good understanding of core algorithms, deep neural networks, and LLMs/SLMs.
• Experience with Azure OpenAI or similar LLM APIs is a plus.
• Experience with NLP and relevant frameworks and libraries is preferred.
• Knowledge of software development processes for machine learning systems with hands-on experience in 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 (Azure would be a plus).
• Familiarity with automation processes and tools such as IaC and CI/CD pipelines.
• Working experience with big data, data lakes/data mesh/lake house architectures, and ML data engineering processes, tools & techniques would be a plus.

Nice-to-haves

• Experience with big data technologies and frameworks.
• Familiarity with data governance and compliance standards.
• Knowledge of financial services industry and its data challenges.

Benefits

• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support.
• Financial coaching.