Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits.
PRINCIPAL ENGINEER – AI PLATFORMS
About Us
Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.
Target's AI Platform organization is building the next generation of enterprise AI capabilities that enable teams to develop, deploy, govern, and operate Machine Learning and Generative AI solutions at scale. Our platform powers AI innovation across the enterprise by providing secure, scalable, and reusable capabilities that accelerate development while maintaining enterprise standards for reliability, governance, and operational excellence.
As a Principal Engineer – ML Operations Platform, you will provide technical leadership in defining the architecture and evolution of our enterprise machine learning platform. You will work across engineering, data science, infrastructure, security, and product organizations to establish scalable patterns for developing, deploying, monitoring, and governing machine learning systems throughout their lifecycle.
This role is ideal for a technology leader who enjoys solving complex platform challenges, influencing engineering strategy, and building capabilities that enable hundreds of engineers and data scientists to deliver AI solutions efficiently and safely.
About the Role:
As a Principal Engineer, you will define the long-term architecture and technical direction for Target's ML Operations Platform. You will establish enterprise-wide standards for machine learning lifecycle management, deployment, governance, observability, and operational excellence while partnering with cross-functional engineering teams to modernize AI platform capabilities. You will influence architecture across multiple organizations, mentor senior engineers, evaluate emerging technologies, and guide strategic platform investments that improve developer productivity and accelerate AI adoption.
Key responsibilities include:
Define the long-term technical strategy and architecture for the enterprise ML Operations Platform.
Design scalable, secure, and resilient cloud-native platforms supporting machine learning workloads.
Establish best practices for model development, deployment, monitoring, and lifecycle management.
Lead architecture for enterprise machine learning infrastructure supporting batch, streaming, and real-time inference.
Drive adoption of cloud-native technologies, Kubernetes, and modern platform engineering practices.
Define standards for model governance, observability, reliability, explainability, and responsible AI.
Partner with infrastructure, security, and engineering teams to improve platform scalability, performance, and operational efficiency.
Evaluate emerging technologies and recommend architectural approaches that improve platform capabilities.
Mentor engineers and influence technical direction across multiple engineering organizations.
Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.
About You:
MS in Computer Science, Engineering, Mathematics, or related technical field with relevant software engineering experience
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
Strong understanding of machine learning lifecycle management, deployment strategies, observability and production operations
Demonstrated experience with machine learning platforms and tooling such as Vertex AI, Kubeflow, MLflow, and/or equivalent technologies
Experience building developer platforms or internal platform products
Experience with distributed training, GPU infrastructure, and large-scale inference platforms
Experience with feature management, model governance, and responsible AI practices.
Familiarity with Generative AI platforms and infrastructure supporting foundation model workloads
Experience with Terraform, GitOps, service mesh technologies, and platform automation
Experience mentoring senior engineers and leading enterprise-scale modernization initiatives
Expertise designing Kubernetes-based platforms supporting AI and machine learning workloads
Strong understanding of software engineering best practices including CI/CD, infrastructure as code, observability, testing, and automation
Experience defining technical strategy, architectural standards and engineering best practices across multiple teams
Excellent communication and influencing skills with the ability to communicate complex technical concepts to engineering and business leaders
Benefits Eligibility
Please paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_FAmericans with Disabilities Act (ADA)
In compliance with state and federal laws, Target will make reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to [email protected]. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed through this channel.
Application deadline is : 08/20/2026Skills Required
- MS in Computer Science, Engineering, Mathematics, or related technical field with relevant software engineering experience
- 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
- Strong understanding of machine learning lifecycle management, deployment strategies, observability and production operations
- Experience with machine learning platforms and tooling such as Vertex AI, Kubeflow, MLflow, and/or equivalent technologies
- Experience building developer platforms or internal platform products
- Experience with distributed training, GPU infrastructure, and large-scale inference platforms
- Experience with feature management, model governance, and responsible AI practices
- Familiarity with Generative AI platforms and infrastructure supporting foundation model workloads
- Experience with Terraform, GitOps, service mesh technologies, and platform automation
- Expertise designing Kubernetes-based platforms supporting AI and machine learning workloads
- Strong understanding of software engineering best practices including CI/CD, infrastructure as code, observability, testing, and automation
- Experience defining technical strategy, architectural standards and engineering best practices across multiple teams
- Excellent communication and influencing skills with the ability to communicate complex technical concepts to engineering and business leaders
Target Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Target and has not been reviewed or approved by Target.
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Healthcare Strength — Health benefits are accessible to hourly team members at relatively low hour thresholds and include no‑cost, 24/7 virtual medical care and expanded mental‑health support. This breadth is positioned as a relative strength compared to typical retail offerings.
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Retirement Support — Retirement programs include a dollar‑for‑dollar 401(k) match with immediate vesting and options like Roth 401(k) and stock purchase. These features strengthen long‑term savings for a wide range of roles.
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Parental & Family Support — Family support includes paid family leave, backup care, and reimbursements for adoption and surrogacy. These resources complement paid time off and holidays for eligible team members.
Target Insights
What We Do
Target is an American retailing company providing access to a wide selection of products such as furniture, electronics, toys, and more. Target is one of the world’s most recognized brands and one of America’s leading retailers. We make Target our guests’ preferred shopping destination by offering outstanding value, inspiration, innovation and an exceptional guest experience that no other retailer can deliver. Target is committed to responsible corporate citizenship, ethical business practices, environmental stewardship and generous community support. Since 1946, we have given 5 percent of our profits back to our communities. Our goal is to work as one team to fulfill our unique brand promise to our guests, wherever and whenever they choose to shop.
