Sr Engineer - MLOps Platform(Remote Or Hybrid)

Target; Brooklyn Park (MN); Hybrid; USD 98,000 - 176,000; Full time

Benefits offered by this job

Health benefits

401(k)

Paid time off

Paid holidays

Employee discount

Job summary

Target is hiring a Senior Engineer on the MLOps Platform team to design, build, and evolve an enterprise platform enabling teams to develop, deploy, and operate ML/Generative AI solutions at scale.

You will collaborate with data scientists, ML engineers, and product teams to deliver secure, reliable, and user-friendly capabilities across the AI/ML lifecycle, from experimentation to production and governance.

Qualifications

• 5+ years of professional software engineering experience building and operating production systems.
• Strong proficiency in Java; Python experience beneficial.
• Experience with REST APIs, microservices, distributed systems, SQL/NoSQL databases, Docker, Kubernetes, Git, and CI/CD.
• Experience building or supporting platforms, developer tooling, or infrastructure services.
• Understanding of the machine learning lifecycle, including experimentation, training, deployment, serving, monitoring, and model management.
• Familiarity with MLOps practices and technologies for production ML systems.
• Experience with cloud platforms; GCP preferred
• Familiarity with Generative AI technologies including LLMs, RAG, embeddings, vector databases, and AI agents.
• Experience enabling self-service developer platforms, SDKs, APIs, or tooling.
• Experience designing scalable platform capabilities.

Responsibilities

• Design, build, test, and operate scalable services for an enterprise MLOps platform.
• Build APIs, microservices, and event-driven systems that support ML and Generative AI workflows.
• Develop platform capabilities for model development, deployment, serving, monitoring, and lifecycle management.
• Enable Generative AI use cases including LLMs, RAG, embeddings, vector search, and agentic applications through reusable platform capabilities.
• Collaborate with Data Scientists, ML Engineers, product managers, and platform teams to build secure, reliable capabilities across the AI/ML lifecycle.
• Build automation and self-service experiences that improve developer and Data Scientist productivity.
• Implement observability, evaluation, governance, security, and reliability across the ML lifecycle.
• Optimize platform services for scalability, availability, performance, and cost.
• Apply strong engineering practices including automated testing, CI/CD, infrastructure automation, and operational excellence.
• Mentor other engineers through design and code reviews.

Skills

Java

Python

REST APIs

Microservices

Distributed systems

CI/CD

SQL/NoSQL

Docker

Kubernetes

Git

Cloud platforms (GCP preferred)

MLOps practices

Generative AI concepts

Tools

Docker

Kubernetes

Git

CI/CD tools

Vertex AI / Gemini Enterprise

Job description

The pay range is $98,000.00 - $176,000.00

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.

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.

About The Role

As a Senior Engineer, you serve as a specialist in the engineering team that supports the product. You help develop and gain insight in the application architecture. You can distill an abstract architecture into concrete design and influence the implementation. You show expertise in applying the appropriate software engineering patterns to build robust and scalable systems. You are an expert in programming and apply your skills in developing the product. You have the skills to design and implement the architecture on your own, but choose to influence your fellow engineers by proposing software designs, providing feedback on software designs and/or implementation. You show good problem solving skills and can help the team in triaging operational issues. You leverage your expertise in eliminating repeat occurrences.

As a Sr Engineer on the MLOps Platform team, you will help design, build, and evolve an enterprise MLOps platform that enables teams to develop, deploy, and operate machine learning and Generative AI solutions at scale.

You will combine strong software engineering and platform engineering fundamentals with an understanding of ML and AI workflows. You will partner with Data Scientists, ML Engineers, product managers, and platform teams to build secure, reliable, and easy-to-use capabilities across the AI/ML lifecycle.

This is a hands-on engineering role focused on building platforms, services, and developer experiences that enable AI/ML teams to move from experimentation to production.

What You Will Do

• Design, build, test, and operate scalable services and capabilities for an enterprise MLOps platform.
• Build APIs, microservices, and event-driven systems that support ML and Generative AI workflows.
• Develop platform capabilities for model development, deployment, serving, monitoring, and lifecycle management.
• Enable Generative AI use cases including LLMs, RAG, embeddings, vector search, and agentic applications through reusable platform capabilities.
• Integrate with cloud AI/ML services, data platforms, model providers, and enterprise systems.
• Build automation and self-service experiences that improve developer and Data Scientist productivity.
• Implement observability, evaluation, governance, security, and reliability capabilities across the ML lifecycle.
• Optimize platform services for scalability, availability, performance, and cost.
• Apply strong engineering practices including automated testing, CI/CD, infrastructure automation, and operational excellence.
• Collaborate across engineering, Data Science, product, security, and infrastructure teams and mentor other engineers through design and code reviews.

Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.

About You

• 5+ years of professional software engineering experience building and operating production systems.
• Strong proficiency in Java or a comparable object-oriented programming language; experience with Python is beneficial.
• Experience with REST APIs, microservices, distributed systems, SQL/NoSQL databases, Docker, Kubernetes, Git, and CI/CD.
• Experience building or supporting platforms, developer tooling, or infrastructure services.
• Understanding of the machine learning lifecycle, including experimentation, training, deployment, serving, monitoring, and model management.
• Familiarity with MLOps practices and technologies for production ML systems.
• Experience with cloud platforms; GCP preferred
• Familiarity with Generative AI technologies including LLMs, RAG, embeddings, vector databases, and AI agents.
• Experience with monitoring, observability, security, and reliability of production systems.
• Ability to independently design and deliver scalable platform capabilities.
• Strong communication and collaboration skills across engineering, Data Science, product, and platform teams.

Desired Qualifications

• Experience building or operating an enterprise MLOps or AI platform.
• Experience with cloud ML platforms such as Gemini Enterprise Agent Platform (Vertex AI) or equivalent technologies.
• Experience with Kubernetes-based ML infrastructure and model serving.
• Experience enabling Generative AI capabilities through shared platforms or services.
• Experience designing self-service developer platforms, SDKs, APIs, or tooling.

This position may be considered for a Remote or Hybrid (known internally at Target as "Flex for Your Day") work arrangement based on Target's needs. A Remote work arrangement means the team member works full-time from home or an alternate location that's not a Target location, does not have a desk at a Target location and may travel to HQ up to 4 times a year. A Hybrid/Flex for Your Day work arrangement means the team member's core role may be performed either remote or onsite at a Target location depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target.

Application deadline is : 09/25/2026