Machine Learning Engineer

About The Company J.P. Morgan, part of JPMorgan Chase & Co., is one of the oldest and most prestigious financial institutions globally, with a history spanning over 200 years. The company offers a comprehensive range of financial services including investment banking, consumer and small business banking, commercial banking, financial transaction processing, and asset management. Serving millions of consumers, small businesses, and prominent corporate, institutional, and government clients worldwide, J.P. Morgan is recognized for its innovative financial solutions and leadership in the financial industry. The firm is committed to fostering a diverse and inclusive work environment, emphasizing integrity, client-centricity, and technological advancement to maintain its competitive edge in the global marketplace. About The Role We are seeking a highly skilled Senior MLOps Engineer to join our dynamic team working on the Recommendation Engine within the Personalization and Insights product suite. In this role, you will collaborate closely with Data Scientists and cross-functional teams to develop, deploy, and maintain scalable machine learning pipelines and infrastructure. Your primary focus will be on building robust systems for distributed model training, real-time and batch inference, hyperparameter tuning, and model monitoring, ensuring high performance and reliability in a cloud environment, predominantly AWS. You will play a pivotal role in optimizing the deployment and operationalization of machine learning models that power personalized experiences across various banking channels, enhancing customer engagement through innovative AI-driven solutions. Qualifications The ideal candidate will possess a strong educational background in Computer Science or related engineering fields, with at least 4 years of experience for candidates holding a Master’s degree, or 6+ years for those with a Bachelor’s degree. Extensive proficiency in Python programming is essential, along with solid fundamentals in cloud computing, preferably AWS. Candidates should have a deep understanding of data science principles, including training and deploying models, as well as operational experience with big data and ML tools such as Ray, Spark, and DuckDB. Familiarity with containerization technologies like Docker, and orchestration systems such as Kubernetes and ECS, is highly desirable. Additionally, experience with monitoring and observability tools, vector databases, and hyperparameter tuning techniques will be advantageous. Candidates should demonstrate an analytical mindset, strong engineering fundamentals, and the ability to work iteratively and action-oriented in a fast-paced environment. Responsibilities Build, deploy, and maintain scalable and reliable pipelines for distributed machine learning training on GPU-enabled clusters, supporting large-scale workflows.Develop and manage high-throughput, real-time inference pipelines, ensuring optimal performance and system reliability.Implement quantization techniques and deploy large language models (LLMs) to improve efficiency and resource utilization.Oversee the management and optimization of vector databases to support advanced AI and ML applications.Establish comprehensive monitoring and observability pipelines to maintain system health, performance, and facilitate rapid issue resolution.Collaborate with cross-functional teams to integrate emerging technologies and continuously enhance existing infrastructure.Partner with product, architecture, and engineering teams to define scalable, high-performance technical solutions aligned with business needs. Benefits J.P. Morgan offers a competitive total rewards package that includes base salary commensurate with experience, skill set, and location. Eligible employees may also receive performance-based incentives, including discretionary bonuses, cash awards, and equity compensation. The company provides a comprehensive benefits program that encompasses health care coverage, on-site health and wellness centers, retirement savings plans, backup childcare, tuition reimbursement, mental health support, and financial coaching. Additional perks include flexible work arrangements, professional development opportunities, and a collaborative work environment designed to foster innovation and growth. The firm is committed to supporting employee well-being and work-life balance, ensuring a rewarding career experience. Equal Opportunity J.P. Morgan is an equal opportunity employer that values diversity and inclusion in the workplace. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, pregnancy, disability, or any other protected attribute under applicable law. We are committed to providing reasonable accommodations for applicants' and employees' religious practices, mental health, or physical disabilities. Our goal is to create a welcoming environment where all employees can thrive and contribute to our collective success. We believe that diverse perspectives drive innovation and excellence, and we are dedicated to fostering an inclusive culture that reflects these values.