Interested in this AI/ML Engineer role at ZENO Group?
Apply Now →About This Role
Zeno Group is the fiercely independent and global, integrated communications agency, born from PR. We bring together the boldest and brightest talent to help clients across industries and sectors unleash the power of strategic communications. Guided by our "Fearless Pursuit of the Unexpected," we push the boundaries to achieve real business value and societal impact for clients. Winner of the industry’s most coveted awards including the 2024 PRWeek U.S. Outstanding Large Agency of the Year, 2023 PRWeek Purpose Agency of the Year, 2022 PRWeek Global Agency of the Year, 2022 PRovoke Best Large Agency to Work For in North America and a three\-time winner of PRWeek’s Best Places to Work. Zeno has also been previously recognized by the Cannes Lions International Festival of Creativity. Zeno is a DJE Holdings Company.
Job Description:
SVP, AI \& Technology Programs
Do you enjoy helping teams rethink how work gets done? Are you energized by guiding organizations through change, facilitating complex conversations and helping people adopt new ways of working through AI and emerging technologies?
As a SVP, AI \& Technology Programs at Zeno, you will play a key role in accelerating AI adoption and business transformation across the agency. Working closely with the Head of AI \& Innovation, practice leaders and client teams, you will help identify opportunities where AI can create meaningful impact, design solutions that fit real\-world workflows and lead programs that drive lasting change.
This is an opportunity for a strategic and hands\-on leader to shape how AI is adopted across the organization, build internal capabilities and help define the future of AI\-enabled communications and client service.
The Team You're Joining:
AI \& Innovation is a growing team building a new practice inside a large organization. We move fast, cover a lot of ground, and hold ourselves to a high standard.
- Craft over speed. Efficiency is table stakes. Everyone has the same AI tools. We take every hour AI saves and reinvest it in work that wasn't possible before. The bar is high because the stakes are high.
- Build what others can't access. What separates us is the proprietary systems, methodology, and data we build in\-house. We license tools when they solve the problem. But the work that differentiates Zeno is built here.
- Makers who can hold a room. This role is not heads\-down. You'll be facilitating workshops with client teams, presenting to senior leadership, and sitting across from practitioners who need you to understand their work before you prescribe anything. We look for people who are strong technically and equally comfortable communicating what they know to people who don't share their vocabulary.
About the Role:
- AI Transformation \& Program Leadership: Lead workflow transformation programs across Zeno's offices, helping teams identify opportunities to improve how work gets done through AI, automation and emerging technologies.
- Workshop Facilitation \& Change Management: Facilitate working sessions with teams and stakeholders to map workflows, identify opportunities for improvement and drive alignment around solutions, ownership and implementation plans.
- AI Enablement \& Training: Design and deliver training programs, workshops and best practices that help employees build confidence, strengthen capabilities and adopt AI\-powered ways of working.
- Technology Evaluation \& Adoption: Evaluate AI tools, platforms and vendor solutions, providing recommendations based on business needs, workflow impact and long\-term organizational value.
- AI Adoption \& Organizational Effectiveness: Monitor adoption, identify barriers and refine programs that drive lasting behavioral change and measurable outcomes.
- Client Innovation \& Strategic Guidance: Support client teams in AI\-related conversations, helping navigate usage standards, implementation considerations and opportunities to enhance client work through AI\-enabled solutions.
- Governance \& Cross\-Agency Collaboration: Help ensure AI tools and workflows align with company policies, responsible AI practices and data privacy requirements while partnering with sister agencies on shared initiatives and learning opportunities.
About You:
- 15\+ years of experience in technology, operations, consulting, organizational transformation or related fields, including experience leading AI, automation or digital transformation initiatives.
- Proven success facilitating workshops and leading large\-scale business transformation initiatives across cross\-functional teams.
- Exceptional communication and presentation skills, with the ability to translate complex technologies into clear, actionable recommendations that build confidence and trust.
- Experience engaging with practitioners, client teams and senior leaders, adapting communication styles to meet the needs of different audiences.
- Strong understanding of AI tools and their practical applications within business environments, with the ability to evaluate solutions based on workflow impact and organizational needs.
- Experience assessing technology solutions and making recommendations regarding implementation, adoption and change management.
- Demonstrated ability to drive alignment, maintain momentum and deliver results across complex initiatives.
- Strong project management and organizational skills, with the ability to manage multiple priorities and stakeholder groups.
- Understanding of communications, marketing, media or professional services environments and the realities of client\-service organizations.
- Curious, collaborative mindset with a passion for learning, problem solving and helping teams embrace new ways of working.
- Commitment to responsible AI adoption and creating meaningful business impact through technology.
Preferred Qualifications:
- Background in change management, organizational development or business transformation.
- Experience designing and delivering training programs across large organizations.
- Familiarity with AI governance, responsible AI frameworks and emerging industry best practices.
- Experience evaluating and selecting technology platforms for organization\-wide deployment.
- Prior experience within public relations, communications, advertising, marketing or related agency environments.
*Pay range: $160,000 to $235,000 USD*
*An employee's pay position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, travel requirements, revenue\-based metrics, any contractual agreements, and business or organizational needs. The range listed is just one component of DJEH's total compensation package for employees. Other rewards may include annual bonuses, a Paid Time Off policy, and region\-specific benefits.*
Level 09
An employee’s pay position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, travel requirements, revenue\-based metrics, any contractual agreements, and business or organizational needs. The range listed is just one component of DJEH’s total compensation package for employees. Other rewards may include annual bonuses, a Paid Time Off policy, and region\-specific benefits.
About Our Benefits
Healthy, happy employees make Zeno better, so we have programs that support physical, mental and financial wellness. Our culture and benefits are designed to promote flexibility, celebrate diversity and support work/life balance. We offer a variety of medical, dental and vision insurance with prescription plans, as well as short and long\-term disability. Our Be Kind to Your Mind program focuses on mental health, providing a paid subscription to Headspace and access to mental health providers and other services through a best\-in\-class employee assistance program. Employees are encouraged to bring their authentic self to Zeno and participate in our employee resource groups which build communities for sharing and support. And while we love our work, we believe in the restorative power of time off with generous vacation, paid holidays and self\-care time. Employees are supported in their pursuit of financial wellness with a 401(k) plan, pretax flexible spending accounts, tuition assistance, life insurance and free access to a certified financial coach. And our unique ZenoFit program provides a monthly allowance to fund activities in your personal life that bring you joy and keep you healthy. These and other benefits are available to non\-temporary employees in the US.
Zeno Group, Inc. provides equal employment opportunities to applicants and employees. Employment decisions are made on the basis of job\-related criteria without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, marital status, age, genetic information, national origin, disability, military, or veteran status, or any other classification protected by applicable law. We invite all applicants to voluntarily self\-identify their race, ethnicity, and gender. Submission of the information on this form is strictly voluntary and refusal to provide it will not subject you to any adverse treatment. Information obtained will be retained in a confidential file and separate from personnel records. This information may only be used in accordance with the provision of applicable federal laws, executive orders, and regulations. If you want more information about any of the sections, please check with a company representative.
Salary Context
This $160K-$235K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At ZENO Group, 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 $181,170 based on 12,692 positions with disclosed compensation. This role's midpoint ($197K) sits 9% above the category median. Disclosed range: $160K to $235K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
ZENO Group AI Hiring
ZENO Group has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $235K - $235K.
Location Context
AI roles in New York pay a median of $211,000 across 2,643 tracked positions. That's 5% above the national 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 $275,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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