Principal Engineer, AI /ML Platform

Target

Confirmed live today High trust
Closes in 5 days Remote

Quick summary

Work type
Remote
Location
Brooklyn Park, MNSunnyvale, CA
Employment
Full-time
Posted
31 days ago
Freshness
Confirmed live today
Closes
Oct 16, 2026 (soon)

Market check

Salary context

How this pay compares to similar roles

Similar $215k
$127k $291k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $180,500–$249,000.

Based on 240 similar postings.

Employer

About Target

Target Corporation is a large-format general merchandise and grocery retailer offering a wide assortment of everyday essentials, apparel, home goods, and electronics through stores and online. Industry: General Merchandise Retail

Target currently has 72 open roles on FindRole.

Listed pay typically runs $98,000–$176,000 across 55 roles with salary data.

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At a glance

TL;DR · Principal Engineer, AI /ML Platform

The Principal Engineer - AI /ML Platform joins the AI Platform organization to provide technical leadership in defining the architecture and evolution of the enterprise machine learning platform. This role involves establishing scalable patterns for developing, deploying, monitoring, and governing machine learning systems throughout their lifecycle. You will design secure, cloud-native platforms supporting batch, streaming, and real-time inference while driving adoption of Kubernetes and modern platform engineering practices. Key responsibilities include defining standards for model governance, observability, and responsible AI. You will utilize technologies such as Vertex AI, Kubeflow, MLflow, Terraform, and GitOps. The role solves the complex problem of building reusable, scalable capabilities that enable hundreds of engineers and data scientists to develop and operate Machine Learning and Generative AI solutions at scale.

What does a Engineer earn in Minnesota?

Median $137000 from 31 postings across 4 companies.

See salary data

What you'll do

  • Define the long-term technical strategy and architecture for the enterprise ML Operations Platform.
  • Design scalable, secure, and resilient cloud-native platforms to support machine learning workloads.
  • Establish best practices for model development, deployment, monitoring, and lifecycle management.
  • Lead the architecture for infrastructure supporting batch, streaming, and real-time inference.
  • Drive the adoption of Kubernetes and modern platform engineering practices across the enterprise.
  • Define standards for model governance, observability, reliability, and responsible AI.
  • Evaluate emerging technologies and recommend architectural approaches to improve platform capabilities.
  • Mentor senior engineers and influence technical direction across multiple engineering organizations.

What we're looking for

  • MS in Computer Science, Engineering, Mathematics, or a related technical field.
  • Extensive experience designing and delivering large-scale cloud-native platforms or distributed systems.
  • Deep experience building and operating enterprise machine learning platforms and MLOps capabilities.
  • Demonstrated experience with machine learning platforms and tooling such as Vertex AI, Kubeflow, MLflow, and/or equivalent technologies.
  • Experience with distributed training, GPU infrastructure, and large-scale inference platforms.
  • Experience with Terraform, GitOps, service mesh technologies, and platform automation.
  • Expertise designing Kubernetes-based platforms supporting AI and machine learning workloads.
  • Experience mentoring senior engineers and leading enterprise-scale modernization initiatives.

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