Lead Software Engineer, ML/Data Platform

JPMorgan Chase

Confirmed live 2 days ago High trust

Quick summary

Work type: On-site
Location: Jersey City, NJ
Posted: 32 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $207k

$174k most similar roles pay here $231k

This listing doesn't post a salary. Most similar roles pay $192,050–$221,100.

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 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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At a glance

TL;DR · Lead Software Engineer, ML/Data Platform

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As a Lead Software Engineer – ML/Data Platform within the Machine Learning Center of Excellence, you will join a multi-disciplinary team to design and deliver production-grade software for complex business problems. You will build end-to-end machine learning model pipelines, engineer data pipelines to ingest and transform large volumes of data, and manage data storage in warehouses and lakes. Your daily work involves deploying systems into production environments, resolving issues within strict SLAs, and driving the adoption of AI-assisted engineering practices for code quality and automation. You will utilize a technical stack including Python, SQL, PySpark, TensorFlow, and AWS services such as S3, Redshift, Kinesis, Firehose, and Glue. Additionally, you will use Terraform for infrastructure design, CI/CD pipelines for deployment, and tools like Langchain or Haystack to support large language model technologies.

Skills

Machine Learning Deep Learning Reinforcement Learning Python SQL PySpark TensorFlow AWS Terraform Amazon S3 AWS Redshift AWS Kinesis AWS Glue CloudWatch CI/CD LangChain Haystack ETL

What you'll do

Design, develop, and maintain production-grade software for enterprise-scale machine learning solutions.
Engineer data pipelines to ingest, transform, and feed large volumes of data into ML model pipelines.
Manage data storage in warehouses and lakes while ensuring high performance and reliability.
Build and implement end-to-end machine learning pipelines from initial data input to final output serving.
Deploy complete systems into production environments and resolve critical issues within a 5-hour SLA.
Drive team adoption of AI-assisted engineering practices to improve code quality, delivery speed, and automation.
Implement infrastructure for large-scale ML deployments using tools like Terraform and AWS services.
Develop and automate high-performance data processing systems using PySpark, TensorFlow, and SQL/Python.

What we're looking for

Formal training or certification in software engineering concepts.
5+ years of applied experience in software engineering.
Experience designing infrastructure for large-scale machine learning deployment using Terraform or AWS Infrastructure as Code.
Proficiency in data manipulation, structuring, and query optimization using SQL and Python.
Experience processing large datasets using PySpark, TensorFlow, multithreading, and multiprocessing.
Expertise in AWS services including S3, Redshift, Kinesis, Firehose, Glue, and CloudWatch for monitoring.
Demonstrated experience leading the use of approved AI-assisted software development tools and ensuring responsible AI practices.
Familiarity with large language model technologies and frameworks like Langchain or Haystack.

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