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Apply Now →About This Role
The pay range is $115,000.00 - $206,000.00 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.
Product Teams at Target are accountable for the delivery of business outcomes enabled through technology and analytic products that are easy to use, easily maintained and highly reliable. Product teams have one shared backlog that is inclusive of all product, technology, discovery and design work.
As Target continues to evolve its digital experience, the On-Platform Agentic Experience team is shaping how emerging AI and agentic capabilities can create simpler, more intuitive, and connected ways for guests to engage with Target across our digital channels. The team is responsible for building a new ecosystem of intelligent experiences that can understand guest needs, connect context and capabilities across the Target experience, and help guests more seamlessly accomplish their goals. This includes defining how agentic experiences show up across the guest journey, identifying the highest-value problems for this technology to solve, and developing the foundational capabilities and experience patterns needed to bring them to life. The team partners closely with UX, Engineering, Data Science, Personalization, enterprise platform teams, and business partners to translate rapidly evolving technology into meaningful guest experiences — balancing experimentation and speed with the scalability, trust, and quality required to shape the future of Target’s digital experience.
As a Senior Product Manager, you will work in the product model and will partner to develop a comprehensive product strategy, related roadmap, and set key business objectives (OKRs) for your respective product. You will need to leverage the knowledge of your product, as well as customer feedback and establish other relevant data points to assess value, develop business cases, and prioritize the direction and desired outcomes for your product. You will lead a product and work in unison with engineers, UX designers, data scientists and business partners to deliver a product.
In this role, you will:
- Own and shape Target’s on-platform agentic experience, defining how AI and agentic capabilities can solve meaningful guest problems and create simpler, more connected experiences across our digital channels.
- Define the product vision, strategy, roadmap, and measurable outcomes for this emerging space, establishing where Target should invest and how the experience should evolve over time.
- Identify and prioritize the highest-value guest problems and use cases, leveraging guest research, behavioral insights, experimentation, and business context to inform product decisions.
- Design for the broader Target ecosystem, connecting experiences, context, data, and capabilities across the guest journey to help guests more seamlessly accomplish their goals.
- Lead the development and delivery of agentic experiences in partnership with UX, Engineering, Data Science, Personalization, platform teams, and business partners, aligning dependencies and priorities across a complex cross-functional landscape.
- Establish the foundational capabilities, product principles, and experience patterns needed to responsibly scale agentic experiences across Target’s digital ecosystem.
- Balance near-term learning and experimentation with long-term platform and capability investments, helping define how agentic technology evolves from emerging use cases into an enduring part of Target’s digital experience.
You will be the “voice of the product” to key stakeholders to ensure that their needs are met, and that the product team is getting the direction and support that it needs to be successful. You will develop and actively understand the market, maintain a product roadmap and backlog outlining the customer themes, epics, and stories while prioritizing the backlog to focus on the highest impact work for your team and stakeholders.
You will encourage the open exchange of information and viewpoints, as well as inspire others to achieve challenging goals and high standards of performance while committing to the organization's direction. You will foster a sense of urgency to achieve goals and leverage resources to overcome unexpected obstacles, and partner with product teams across the organization to help them achieve their goals while pursuing and completing yours.
Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.
About you:
- Four-year degree or equivalent experience
- 6+ years of digital product management experience
- Deep curiosity about emerging technology and consumer behavior, with a strong understanding of evolving trends in AI, agentic experiences, and the broader digital landscape.
- Ability to thrive in ambiguity, create clarity in emerging spaces, and make informed product decisions when established patterns or playbooks do not yet exist.
- Strong systems thinking, with the ability to connect macro trends and ecosystem opportunities to the detailed product, experience, and technology decisions required to bring a vision to life.
- Strong product judgment, with the ability to distinguish meaningful guest value from technology-driven novelty and make thoughtful tradeoffs with incomplete information.
- Demonstrated ability to influence and build alignment across complex, highly cross-functional initiatives with multiple teams, dependencies, and stakeholders.
- Experience with technology and ability to facilitate communication between business and technology teams
- Experience working in an agile environment (e.g., user stories, iterative development, scrum teams, sprints, personas)
- Ability to lead a body of work with cross-functional partners
- Strong communication skills
This position will operate as a Hybrid/Flex for Your Day work arrangement based on Target’s needs. A Hybrid/Flex for Your Day work arrangement means the team member’s core role will need to be performed both onsite at the Target HQ MN location the role is assigned to and virtually, 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. Click here if you are curious to learn more about Minnesota.
Benefits Eligibility
Please paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_EAmericans 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.
Salary Context
This $115K-$206K range is below the median for AI/ML Engineer roles in our dataset (median: $178K across 1623 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Target, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $211,950 based on 13,048 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($160K) sits 24% below the category median. Disclosed range: $115K to $206K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Target AI Hiring
Target has 7 open AI roles right now. They're hiring across MLOps Engineer, AI/ML Engineer, AI Software Engineer. Positions span Brooklyn Park, MN, Brooklyn Park, MN, US, Minneapolis, MN, US. Compensation range: $176K - $356K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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