Senior Lead Software Engineer, AI/ML Developer

JPMorgan Chase

Confirmed live today Trusted

Quick summary

Work type: On-site
Location: Jersey City, NJ
Employment: Full-time
Posted: 18 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $176k

$107k $244k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $150,187–$202,561.

Based on 240 similar postings.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1226 open roles on FindRole.

Listed pay typically runs $156,750–$215,000 across 5 roles with salary data.

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At a glance

TL;DR · Senior Lead Software Engineer, AI/ML Developer

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As a Senior Lead Software Engineer - AI/ML Developer within the Consumer & Community Banking's AI/Machine Learning Platform Engineering Team, you will join an agile team focused on building, scaling, and maintaining robust machine learning platforms. You will design and deliver infrastructure and tools that empower data scientists to develop, deploy, and monitor models efficiently. Your daily responsibilities include implementing production code for platform services, APIs, and automation pipelines, while managing model training, deployment, and lifecycle monitoring. You will utilize Python, TensorFlow, PyTorch, Scikit-learn, Spark, Pandas, and SQL. The role requires expertise in MLOps, CI/CD, and cloud-based platforms like AWS SageMaker or Azure ML. You will solve technical problems regarding scalable ML workflows, feature management, and infrastructure provisioning using Docker, Kubernetes, and Airflow.

Skills

Python TensorFlow PyTorch Scikit-learn MLOps Spark Pandas SQL AWS SageMaker GCP AI Platform Azure ML Databricks Snowflake Docker Kubernetes Airflow Terraform CloudFormation CI/CD RESTful APIs Agile

What you'll do

Design, build, and maintain scalable machine learning platforms and infrastructure for end-to-end ML workflows.
Develop and optimize tools for model training, deployment, monitoring, and lifecycle management.
Integrate data engineering, feature management, and model serving capabilities into unified platform solutions.
Implement secure, high-quality production code for platform services, APIs, and automation pipelines.
Automate infrastructure provisioning, configuration, and CI/CD pipelines for ML platform services.
Produce architecture and design artifacts for platform components aligned with enterprise standards.
Drive team adoption of AI-assisted engineering practices to improve code quality and delivery speed.
Ensure platform reliability and performance through proactive monitoring and continuous troubleshooting.

What we're looking for

Formal training or certification on software engineering concepts and 5+ years of applied experience.
Hands-on experience building, deploying, and maintaining machine learning platforms or infrastructure.
Advanced proficiency in Python and one or more ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Experience with data processing frameworks and tools including Spark, Pandas, and SQL.
Practical experience with cloud-based ML platforms (AWS SageMaker, GCP AI Platform, Azure ML) or on-prem ML infrastructure.
Strong understanding of MLOps practices, including CI/CD for ML, model versioning, and monitoring.
Proficiency in all aspects of the Software Development Life Cycle and Agile Methodologies.
Experience with containerization and orchestration tools (e.g., Docker, Kubernetes, Airflow) (preferred).

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