Senior ML Platform Engineer – AI/ML Infrastructure

Aumni

Jersey City (NJ)

Sur place

USD 180 000 - 240 000

Plein temps

14 jours+

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Résumé du poste

JPMorgan Chase is seeking a Senior Lead Software Engineer to drive a robust ML platform within its AI/ML Platform Engineering Team. You will design, build, and scale infrastructure to empower data scientists and ML engineers to safely develop, deploy, and monitor models.

Emphasis on secure production code, CI/CD pipelines, and enterprise-standard practices across multiple platforms. The role requires hands-on Python, ML framework experience, and deep knowledge of data processing, cloud ML

Qualifications

  • Formal training or certification on software engineering concepts.
  • Hands-on experience building, deploying, and maintaining machine learning platforms or infrastructure.
  • Proficient in Python and ML frameworks; strong understanding of SDLC and Agile methodologies.

Responsabilités

  • Designs, builds, and maintains scalable ML platforms and infrastructure to support end-to-end ML workflows.
  • Develops and optimizes tools for model training, deployment, monitoring, and lifecycle management.
  • Integrates data engineering, feature management, and model serving capabilities into unified ML platform solutions.
  • Implements secure, high-quality production code for platform services, APIs, and automation pipelines.
  • Leads evaluation sessions with data scientists, ML engineers, and product teams to understand requirements and deliver platform features.

Connaissances

Python
TensorFlow
PyTorch
Scikit-learn
Spark
SQL
Agile Methodologies
API development

Formation

Bachelor's degree in Computer Science or related

Outils

AWS SageMaker
GCP AI Platform
Azure ML
Docker
Kubernetes
Databricks
Snowflake
Terraform

Description du poste

JPMorgan Chase is seeking a Senior Lead Software Engineer to drive a robust ML platform within its AI/ML Platform Engineering Team. You will design, build, and scale infrastructure to empower data scientists and ML engineers to safely develop, deploy, and monitor models.

Emphasis on secure production code, CI/CD pipelines, and enterprise-standard practices across multiple platforms. The role requires hands-on Python, ML framework experience, and deep knowledge of data processing, cloud ML

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