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About This Role
About the Team
Marketing brings our brand to life through deep expertise and an authentic love for pets. The team is dedicated to delivering personalized experiences for our consumers, supported by best\-in\-class, data\-driven marketing capabilities.
The work spans key areas including Loyalty, Customer Analytics \& Research, Brand Experience \& Creative, and Omni\-Channel Marketing. Each team member brings a unique perspective, working together to create meaningful and engaging experiences for both pets and pet parents.
About the Location
Collaborative Work Environment:
At PetSmart, teamwork and connection are core to how we thrive. This role is based at our Phoenix Home Office, with an expectation of working a minimum of four days in the office each week. In a standard work week, associates may work up to one remote “flex day” (with leader approval). Our hybrid approach is designed to foster strong collaboration while also supporting flexibility and individual success.
About the Job
The Manager, Campaign Management will work on the Omni\-Channel Marketing \& Personalization Operations team alongside campaign specialists, Direct Marketing Managers, HTML developers, and database analysts to execute all aspects of our omni\-channel marketing and personalization strategy across email, SMS, and push. This role will support a wide range of initiatives, from simple promotional campaigns to highly dynamic, data\-driven automations with cross\-channel orchestration.
### Primary Responsibilities
- Bring campaign deployment expertise to support and execute day\-to\-day campaign builds across email, SMS, and push, including data imports, quality assurance, stakeholder approvals, requirements validation, and deployment
- Review project requests from business stakeholders to determine implementation approach using established processes and best practices, and scope production requirements as needed
- Partner with campaign specialists and Direct Marketing Managers to continuously improve campaign execution processes, ensuring accuracy and adherence to best practices
- Lead, mentor, and develop Campaign Specialists
- Execute and optimize cross\-channel communications, including SMS and push notifications
- Serve as the subject matter expert for Salesforce Marketing Cloud (SFMC), including capabilities, limitations, and best practices for campaign and journey development
- Communicate SFMC capabilities effectively to marketing partners to inform campaign design and execution
- Analyze campaign performance data and report insights to business stakeholders
- Support the execution and deployment of journeys within Journey Builder
- Interpret strategic briefs and recommend effective deployment tactics, including audience segmentation, journey setup, and SFMC functionality
- Collaborate with IT partners as needed to support campaign execution and data processes
### Qualifications
- 4–6 years of experience in email, lifecycle, or omni\-channel marketing
- Proven ability to thrive in a fast\-paced environment, maintain composure under pressure, and deliver high\-quality work
- Bachelor’s degree in Marketing, Information Technology, or a related field
- Hands\-on experience with Salesforce Marketing Cloud (SFMC), including journeys, automations, and ad hoc deployments
- Strong commitment to delivering exceptional customer experiences
- High attention to detail and organizational skills
- Ability to manage time effectively, follow direction, work independently, and lead a team
- Experience with reporting tools and Einstein within SFMC
Additional Job Considerations
- This role requires collaboration, teamwork, and face\-to\-face interaction with colleagues, leaders, and/or clients.
- Being in the office ensures access to leaders, cross\-functional partners, and resources necessary to make timely decisions and drive results.
- On\-site presence in accordance with our FlexSmart policy supports our culture of innovation, mentorship, and engagement, which is integral to our success in developing the best team.
\* *This is not intended to be an all\-inclusive, exhaustive list of all essential job functions for this position. PetSmart retains the right to change or assign other required job duties to this position.*
About the Culture
At PetSmart, Anything for Pets begins with our people. Every associate plays a vital role in creating meaningful experiences for pets and their families, and we empower our teams with the tools, resources, and opportunities to grow and succeed.
We’re more than a workplace, we’re Team PetSmart. Together, we grow, collaborate, and challenge ourselves to be the best in all we do. Our culture is built on belonging and shared purpose, where every voice and experience matters. Guided by our values, we strive to do what’s right, lead responsibly, and bring our passion for pets to life every day. Not sure if you meet 100% of the position requirements and whether you should apply? We’d still like to hear from you and encourage you to apply with us! You might be the right fit for this role or another opportunity across Team PetSmart.
Our home office offers outstanding amenities in a fun and rewarding workplace including:
- Pet\-friendly environment , bring your pets to work and enjoy the on\-site dog park!
- On\-Site Events \& Adoptions , enjoy community\-building opportunities, including pet adoption days, seasonal celebrations, family events, art events, \& holiday festivals
- “Top Dog” gym with equipment, fitness classes, massage therapists, personal trainers, and wellness spaces
- “Sit \& Stay” Café serving fresh breakfast and lunch options, snacks, \& more
- “ Lil Paws” NAEYC\-accredited onsite childcare facility providing high\-quality early education
- Paid Volunteer Opportunities to spend time doing good for causes close to heart
- Print Center and Business Services , Dry Cleaning, Mother's Rooms, Sustainable Infrastructure \& more
PetSmart provides an equal opportunity for all associates and job applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status or other legally protected characteristics.
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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At PetSmart, 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 Required
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 $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
PetSmart AI Hiring
PetSmart has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Phoenix, AZ, US, Valley Stream, NY, US. Compensation range: $79K - $79K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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