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We are looking for a seasoned campaign professional with deep roots in state and local politics who can translate a national campaign vision into tailored, market\-specific plans that win — and who thrives in a matrixed environment where success depends on rallying internal cross\-functional partners around a shared mission. The ideal candidate has run or managed local and statewide campaigns, built coalitions at the local level, and knows how to drive alignment across diverse stakeholders both inside and outside an organization.As a State Campaign Manager on Meta's Public Affairs team, you will play a critical role in driving one of the company's most strategic initiatives: building public understanding and support for AI at the state and local level. You'll be embedded in an incredibly strong team tackling some of the most important challenges the company faces — and your work will directly shape the campaign's success.In this role, you will quarterback the development and execution of state and local campaign strategy for Meta's AI advocacy efforts, ensuring our message resonates with key audiences — from state legislators and local officials to community stakeholders and grassroots organizations. Equally important, you will serve as the connective tissue across Meta's internal campaign functions — communications, marketing, policy, research, and legal teams to ensure the company's resources are aligned behind your state\-level campaign plans.
### State Campaign Manager, Public Affairs \- AI Campaign Responsibilities:
- Serve as the single\-threaded owner for state and local AI campaign execution, defining the vision and strategy for your designated market(s) and driving cross\-functional alignment on the ground.
- Act as the primary quarterback across Meta's communications, marketing, policy, legal, research, and product teams to ensure seamless campaign execution at the state and local level — synthesizing inputs, driving alignment, and maintaining a unified campaign narrative.
- Build and maintain strong internal relationships across functions, ensuring that campaign strategies are translated into coordinated state\-level action and that cross\-functional team insights flow back to inform planning.
- Develop and execute localized campaign plans — including earned media, paid media, grassroots/grass\-roots engagement, and legislative outreach — that advance Meta's AI narrative and priorities at the state and local level.
- Act as a practical, hands\-on campaign leader who can translate strategy into actionable state\-level tactics with clear milestones and accountability.
- Monitor state legislative and regulatory developments related to AI and technology policy, and adapt campaign strategy in real time to address emerging issues.
- Deploy campaign resources effectively across paid, earned, and grassroots channels to maximize impact in priority states and localities.
- Convene and lead regular cross\-functional syncs to ensure all internal teams are operating from the same playbook, flag dependencies, and drive accountability across workstreams.
- Build repeatable best practices for state\-level campaign execution and cross\-functional coordination that can scale across multiple markets.
### Minimum Qualifications:
- 8\+ years of experience in political campaigns, public affairs, or government relations, with a strong emphasis on statewide and local campaign management
- Demonstrated experience managing or serving in a senior role on at least one statewide campaign (gubernatorial, senatorial, ballot initiative, or statewide issue advocacy)
- Proven track record running field operations, coalition\-building, or voter/public engagement programs at the state or local level
- Experience coordinating across multiple internal functions or departments (e.g., comms, policy, legal, marketing) to deliver integrated campaign outcomes
- Experience working with or influencing state legislatures, governors' offices, or local government bodies
- Ability to manage multiple cross\-functional workstreams simultaneously with a campaign\-speed mindset
- Comfortable interacting with and influencing senior leadership, elected officials, and diverse community stakeholders
### Preferred Qualifications:
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
- Direct experience managing a statewide political campaign (candidate or issue\-based) as campaign manager, political director, or field director
- Proven success operating in a large, matrixed organization where campaign outcomes depend on coordinating across teams you don't directly manage — rallying internal partners through influence, clarity, and shared purpose
- Experience running state or local issue advocacy campaigns, ideally in technology, innovation, or economic development
- Track record of building effective grassroots and grasstops coalitions in multiple states or regions
- Familiarity with the AI policy landscape and the ability to communicate complex technology topics in accessible, locally relevant terms
- Exceptional leadership skills with a willingness to take initiative, be scrappy, and operate with a high degree of autonomy and judgment
- Sound strategic instincts combined with hands\-on execution — you're as comfortable building a state\-level plan as you are leading an internal cross\-functional alignment meeting
- Experience communicating complex policy positions into concise, credible messages for state and local audiences, media, and government officials
- Broad understanding of the political, economic, and public opinion dynamics that shape state\-level policy and decision\-making
- Courage and conviction to challenge and defend ideas, and the adaptability to shift strategy as conditions on the ground evolve
### About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E\-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations\[email protected].
$176,000/year to $247,000/year \+ bonus \+ equity \+ benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
Salary Context
This $176K-$247K range is above the median for AI/ML Engineer roles in our dataset (median: $175K across 2162 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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Meta, 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 $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. Disclosed range: $176K to $247K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Meta AI Hiring
Meta has 40 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer, Research Scientist, AI Product Manager. Positions span Seattle, WA, US, Menlo Park, CA, US, New York, NY, US. Compensation range: $181K - $403K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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