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Policy Enforcement Jobs (NOW HIRING)

Apton Inc

Network Administrator

Atlanta, GA ยท On-site

Provides expert leadership in managing, securing, and optimizing Fortigate Firewall deployments, ensuring robust threat protection, policy enforcement, and alignment with enterprise security ...

K-Tek Resourcing LLC

Digital Network Admin

Seattle, WA ยท On-site

... security, policy enforcement, and seamless integration with enterprise security frameworks. ยท Provides expert leadership in managing, securing, and optimizing Fortigate Firewall deployments ...

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Policy Enforcement information

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$53K

$131.7K

$146K

How much do policy enforcement jobs pay per year?

As of Aug 16, 2026, the average yearly pay for policy enforcement in the United States is $131,692.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $145,000.00 per year, depending on experience, location, and employer.

How does a policy enforcement professional typically collaborate with other departments to ensure compliance?

Policy Enforcement professionals routinely work with departments such as Legal, Human Resources, and Operations to interpret and implement organizational policies. They facilitate training sessions, provide guidance on compliance issues, and ensure that all teams are aware of updated regulations. Regular cross-departmental meetings and open channels of communication are essential for addressing concerns quickly and maintaining a consistent standard of compliance throughout the organization.

What is a policy enforcement?

Policy enforcement jobs refer to positions responsible for ensuring that laws, regulations, organizational standards, or internal policies are followed. These roles can be found in government agencies, law enforcement, corporate compliance departments, and regulatory bodies. Individuals in policy enforcement may conduct investigations, monitor activities, educate others about rules, and take corrective actions when violations occur. Their work is essential for maintaining legal and ethical standards within organizations and society.

What is the difference between Policy Enforcement vs Policy Analyst?

AspectPolicy EnforcementPolicy Analyst
Required CredentialsTypically a bachelor's degree in criminal justice, public administration, or related fieldsUsually a bachelor's or master's degree in public policy, political science, or related areas
Work EnvironmentFieldwork, law enforcement agencies, government officesOffice-based, research, and analysis settings
Employer & Industry UsageGovernment agencies, law enforcement, regulatory bodiesThink tanks, government departments, consulting firms

Policy Enforcement focuses on implementing and ensuring compliance with policies, often involving fieldwork and direct interaction with the public. Policy Analysts primarily research, evaluate, and develop policies through analysis and data interpretation. Both roles are essential in the policy-making process but differ in their focus and work environment.

What are the key skills and qualifications needed to thrive in policy enforcement, and why are they important?

To thrive in Policy Enforcement, you need a strong understanding of relevant regulations, compliance procedures, and investigative techniques, often supported by a background in criminal justice, law, or public administration. Familiarity with case management systems, incident reporting software, and regulatory databases is typically required. Integrity, attention to detail, and effective communication are essential soft skills for building trust and ensuring clear, unbiased enforcement actions. These skills ensure policies are upheld consistently, legal standards are maintained, and organizational or public safety is protected.
More about Policy Enforcement jobs

What job categories do people searching Policy Enforcement jobs look for?

The top searched job categories for Policy Enforcement jobs are:

Policy Enforcement jobs near you
Infographic showing various Policy Enforcement job openings in the United States as of August 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution, with an average salary of $131,692 per year, or $63.3 per hour.

Staff Machine Learning Engineer - Policy & Safety

Spotify

New York, NY

$227K - $324K/yr

Full-time

Medical, Retirement, PTO

Re-posted 12 days ago

Job description

We design Spotify's consumer experience-end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints-from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.

About the Team
The Policy & Safety team sits within the Content Platform domain and builds the systems that keep Spotify safe and trustworthy at scale. We own the infrastructure behind content moderation, including detection models, policy enforcement systems, compliance pipelines, and the safety-by-default platform.

Our work sits on the critical path of every new content type and product experience-from messaging and comments to collaborative and agentic features. We partner closely with Trust & Safety, Legal, and Public Affairs to ensure that as Spotify evolves, safety is built in from the start-not added later.

What You Will Do
  • Build and scale machine learning systems for proactive content detection, classification, and pre-publish safety scanning
  • Design and implement policy evaluation frameworks, including standardized datasets, offline and online metrics, and continuous improvement loops
  • Develop multimodal models that combine text, audio, image, and video signals for safety and policy enforcement
  • Architect feedback loops that turn human reviewer input into structured training data for continuous model improvement
  • Translate regulatory requirements (e.g., precision/recall obligations, compliance reporting) into scalable ML system designs
  • Partner with cross-functional teams across Trust & Safety, Legal, Public Affairs, and Product to deliver safe user experiences
  • Drive technical direction in ambiguous problem spaces and contribute to long-term platform architecture
  • Mentor and support other machine learning engineers, helping raise the bar across the team
Who You Are
  • You have experience building and shipping production-grade machine learning systems at scale
  • You have strong expertise in ML evaluation, including dataset design, metrics, and model performance monitoring
  • You have worked with multimodal machine learning systems across text, audio, image, or video domains
  • You are experienced with human-in-the-loop systems, active learning, or feedback-driven model improvement
  • You are comfortable translating complex requirements into technical solutions, including regulatory or policy constraints
  • You have experience working across teams and influencing technical direction in large-scale systems
  • You are comfortable navigating ambiguity and making thoughtful decisions that balance speed, quality, and risk
  • You communicate clearly and collaborate effectively with both technical and non-technical stakeholders
Where You Will Be
  • This role is based in New York, NY
  • We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.
The United States base range for this position is $227,495-$324,993 USD, plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, and paid sick leave. These ranges may be modified in the future.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice
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