Manager of Software Engineering - Machine Learning Platform at JPMC Candidate Experience page

Palo Alto, California, United States -

Full Time

Start Date

Immediate

Expiry Date

21 May, 26

Salary

215000.0

Posted On

20 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Software Engineering, Machine Learning Platforms, Leadership, Project Delivery, ML Infrastructure, Python, TensorFlow, PyTorch, Scikit-learn, Spark, Pandas, SQL, Cloud ML Platforms, MLOps, APIs, CI/CD

Industry

Financial Services

Description

Elevate your career by leading high-impact engineering teams and shaping the future of machine learning platforms at JPMorgan Chase, driving innovative solutions that empower data scientists and ML engineers across the organization. As a Manager of Software Engineering at JPMorgan Chase in the Consumer and Community Banking Technology team, you will set strategic direction, oversee project delivery, and ensure alignment with business objectives for multiple engineering teams. Leveraging your leadership and technical expertise, you will guide the development of robust ML infrastructure and tools, foster a culture of technical excellence, and drive continuous improvement in platform capabilities. Your role will require exceptional collaboration and stakeholder management skills, as you empower teams, champion best practices, and represent the ML platform engineering function in cross-functional forums. Job Responsibilities Lead and manage engineering teams in the design, development, and maintenance of scalable machine learning platforms and infrastructure. Set strategic direction for ML platform initiatives, ensuring alignment with business goals and enterprise standards. Oversee the delivery of tools for model training, deployment, monitoring, and lifecycle management. Guide the integration of data engineering, feature management, and model serving capabilities into unified ML platform solutions. Ensure the implementation of secure, high-quality production code for platform services, APIs, and automation pipelines. Collaborate with data scientists, ML engineers, product teams, and business stakeholders to define requirements and deliver impactful platform features. Drive platform reliability, scalability, and performance through proactive monitoring, troubleshooting, and continuous improvement. Oversee architecture and design documentation for platform components. Champion automation of infrastructure provisioning, configuration, and CI/CD pipelines for ML platform services. Foster a culture of technical excellence, innovation, and continuous learning within the engineering team. Represent the ML platform engineering function in cross-functional forums and contribute to the community of practice. Required Qualifications, Capabilities, and Skills 5+ years of applied experience or formal training/certification in software engineering concepts, including coaching and mentoring. Proven experience building, deploying, and maintaining machine learning platforms or infrastructure. Proficiency in Python and familiarity with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with data processing frameworks and tools (e.g., Spark, Pandas, SQL). Strong understanding of cloud-based ML platforms (e.g., AWS SageMaker, GCP AI Platform, Azure ML) or on-prem ML infrastructure. Knowledge of MLOps practices, including CI/CD for ML, model versioning, and monitoring. Experience developing APIs and platform services for ML workflows. Solid understanding of the software development life cycle, agile methodologies, and engineering best practices. Demonstrated ability to lead and mentor engineering teams, and collaborate with cross-functional stakeholders. Preferred Qualifications, Capabilities, and Skills Experience with Databricks for scalable data engineering and ML platform integration. Experience with Snowflake for cloud-based data warehousing and analytics. Exposure to Snorkel AI for programmatic data labeling and training data management. Experience with containerization and orchestration tools (e.g., Docker, Kubernetes, Airflow). Familiarity with feature stores, model registries, and ML metadata management. Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation). Experience with RESTful APIs and microservices architectures. This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorgan Chase’s review of criminal conviction history, including pretrial diversions or program entries. Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. Equal Opportunity Employer/Disability/Veterans Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.

Responsibilities

The role involves leading and managing engineering teams in designing, developing, and maintaining scalable machine learning platforms and infrastructure, while setting the strategic direction for ML platform initiatives aligned with business goals. Responsibilities also include overseeing the delivery of tools for model training, deployment, monitoring, and lifecycle management, ensuring secure, high-quality production code.