Overview
We are seeking a Senior MLOps Engineer to collaborate closely with Data Scientists to design and deploy machine learning models on a modern MLOps stack. As the Lead Machine Learning Engineer on the Recommendation Engine team, you will build and maintain pipelines for distributed model training on large compute clusters, manage batch and real-time model serving, scale hyperparameter tuning, monitor production models, and validate deployments within a well governed environment.
Our Personalization and Insights product delivers high throughput, low latency applications that leverage advanced ML architectures and run on AWS. These solutions power personalized experiences across Chase Consumer & Community Banking channels, combining traditional banking services with interactions in Travel, Merchant Offer Shopping, and Dining spaces.
Location: New York, NY 10001
Key responsibilities
- Build, deploy, and maintain robust pipelines for distributed training on GPU-enabled clusters to support scalable ML workflows.
- Develop and manage real-time and batch inference pipelines to ensure high performance and reliability.
- Apply quantization techniques and deploy large language models to maximize efficiency and resource utilization.
- Oversee the management and optimization of vector databases for advanced AI and ML applications.
- Establish and maintain comprehensive monitoring and observability pipelines to ensure system health and rapid issue resolution.
- Collaborate with cross functional teams to integrate new technologies and continuously improve existing infrastructure.
- Partner with product, architecture, and other engineering teams to define scalable and performant technical solutions.
Required qualifications, capabilities, and skills
- BS in Computer Science or related Engineering field with 6+ years of experience, or MS in Computer Science or related Engineering field with 4+ years of experience.
- Strong proficiency in Python and cloud computing, preferably AWS.
- Understanding of quantization techniques such as PTQ, AWQ, etc., used to accelerate LLM inference on targeted GPU architectures.
- Experience in systems engineering fundamentals: caching, CUDA, autoscaling, high throughput, low latency, and cross-region resilient applications.
- Deep knowledge of data science fundamentals and experience training and deploying models.
- Experience with monitoring and observability tools to track model input/output and feature statistics.
- Operational experience with big data/ML tools such as Ray, DuckDB, Spark, and in training/inference systems like Ray, vllm/SGLang.
- Solid engineering fundamentals and an analytical mindset.
Preferred qualifications, capabilities, and skills
- Experience with recommendation and personalization systems is a plus, CUDA experience is highly desirable.
- Strong fundamentals and experience with containers (Docker ecosystem) and container orchestration systems such as Kubernetes and ECS, plus DAG orchestration tools like Airflow and Kubeflow.
- Good knowledge of databases.
Salary and benefits
Salary is a base figure determined by the role, experience, skill set, and location. Eligible roles may include commission-based pay and/or discretionary incentive compensation, paid in cash and/or forfeitable equity based on individual performance. The package also comprises a range of benefits, including comprehensive health care coverage, on-site health and wellness facilities, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching, and more. Details about total compensation and benefits will be provided during the hiring process.
About us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s leading corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans more than 200 years, and we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We recognize that our people are our strength, and our diverse talents contribute to our success. We are an equal opportunity employer and value diversity and inclusion. We do not discriminate based on protected attributes and we provide accommodations for applicants and employees as needed. Equal Opportunity Employer, including Disability/Veterans.
About the team
J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions worldwide rely on us for strategic advice, capital raising, risk management, and liquidity support in more than 100 countries.