Applied AI ML Lead - ML Ops, CTC

JPMorgan Chase & Co. • Jersey City, NJ

7h

About The Position

Step into a fast-growing area of Cybersecurity at JPMorganChase, where you can
help build and deploy machine learning solutions that directly support Cyber
Operations. In this role, you’ll work independently and apply your skills in
data analysis, statistics, and data engineering to deliver machine learning
models that drive real business outcomes. You’ll join a global Cybersecurity
team, collaborating with technologists and innovators who protect our assets
every day.

As an ML Ops Engineer within Corporate Sector in Cybersecurity & Tech Controls
team,  you will deploy, monitor, and manage machine learning models in
production environments using the latest technologies. You’ll automate model
deployment, optimize infrastructure, and ensure AI systems perform reliably and
efficiently. Your collaboration with cross-functional teams and your
problem-solving skills will help drive innovation and deliver impactful AI
solutions.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field, with relevant ML Ops experience.
• Experience deploying and managing machine learning models in production environments.
• Skilled in building and maintaining CI/CD pipelines for machine learning workflows.
• Proficient with cloud platforms (AWS, Google Cloud, Azure) and containerization tools (Docker, Kubernetes).
• Familiar with monitoring and logging tools (Prometheus, Grafana, ELK Stack).
• Advanced Python programming skills.
• Strong problem-solving skills and attention to detail.
• Effective communicator, able to collaborate with cross-functional teams.
• Bachelor’s degree in Computer Science, Engineering, or a related field, with relevant ML Ops experience.

Nice To Haves

• Experience deploying and managing large-scale machine learning models in production.
• Ability to monitor models in production and address performance and data quality issues.
• Working knowledge of security best practices and compliance standards for ML systems.
• Experience optimizing infrastructure for performance and efficiency.
• Developed REST APIs using frameworks like Flask or FastAPI.
• Familiarity with synthetic datasets for model training and evaluation.

Responsibilities

• Work closely with data scientists and software engineers to integrate machine learning models into applications.
• Deploy machine learning models into production, ensuring they are scalable, reliable, and efficient.
• Build and maintain CI/CD pipelines to automate testing, deployment, and updates for machine learning models.
• Manage and optimize infrastructure for running models, including cloud services, Docker, and Kubernetes.
• Set up monitoring and logging to track model performance, detect anomalies, and ensure smooth operation.
• Maintain version control for models and data, supporting traceability and compliance.
• Apply security best practices and ensure models meet regulatory standards.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees