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About This Role
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TRANSFORMATION | AI Executive Producer — Film & Video Solutions
Our work is bundled by teams, not by organizational layers. But it's not all work. Everyone at Monks knows how to have a good time, and everyone contributes to the positive energy of our culture. If you're intrigued, read on as we may have the dream job for you.
As the AI Executive Producer for AI Film & Video Solutions, you are accountable for the direction, motivation, and financial impact of the team delivering our Global AI Film & Video solution — AI-driven film, video, and motion content produced at scale for the world's biggest brands.
You oversee AI Solution Managers and production teams in pitching and executing film and video work within or across platforms, providing leadership and expert knowledge of the talent, techniques, and technology necessary to execute the work. You run AI production the way a great EP runs a traditional film shoot: everything approved before generation, with structured intake (talent, pose, wardrobe, product, direction, background) as the efficiency lever that makes scale possible.
You are responsible for attracting, developing, and deploying internal production talent to ensure the best content and production value possible for the idea and the client. You are accountable for the overall quality of work, ensuring goals are met and projects are delivered on time, on budget, and within margin targets.
The AI Executive Producer has 8–10+ years of experience across film, video, social, and digital content and has worked in film, photo, and post production capacities. You are a creative problem solver whose production expertise allows you to guide complex development efforts across AI/Innovation funnels — from image-to-video pipelines to fully agentic film production.
You possess strong leadership skills to help build out the Transformation COE team activities, with a focus on comms management, R&D, education, sales, and execution.
You are a great communicator, motivator, and project manager with an innate ability to get things done — leading from the front and setting a strategic environment that allows producers to excel.
As a result, you wear many hats. You take a very proactive role in business development efforts, helping to prepare and present both written and oral presentations. You advise project teams and clients on best practices, process, scope, schedules, and pricing, while building strong, resilient relationships along the way.
You develop, build, and/or evolve operational processes and workflow documentation, for all successful R&D to be implemented into the Monks.Flow pipeline after graduation has been determined. You manage micro AI production squads — the standard shape being CD, Producer, Creative Technologist, AI artist/retoucher, and 3D artist — to deliver product innovation on quarterly timelines. Quarterly, you track, review, and set new goals based on how the AI landscape develops in markets.
You will work closely with the Operations & Casting teams in conjunction with the Scaled Client Leads to manage current workloads as well as best forecast incoming projects to secure adequate resources.
RESPONSIBILITIES
- Sales: Drive sales and creative development processes with an AI-enabled/forward production-led mentality. Ensure we show up competitive and set apart by bringing AI film and video production and operations capabilities into the pitch process, with all pitches connected to the global vision and strategy. Be the face and a consistent voice representing the studio to other caps and disciplines to ensure everyone is aware of the latest and greatest.
- Vision: Innovation is at the heart of everything that we do; our process and client solutions will offer digital first solutions in the creative/origination process. All pitches are accompanied with detailed production approaches that align to the overall vision and drive production innovation.
- Innovation: Ensures that all AI processes are deployed and delivered on, in collaboration with other Monks.Flow, Innovation, SME and Tech teams — moving at the pace of the market as video models and motion pipelines evolve.
- Operations: Build, implement and enhance AI film/video production delivery processes — including QC gates, human review checkpoints, and legal/compliance review workflows (side-by-side validation, AI counsel sign-off).
- Benchmarking: Support tracking on existing productions before and after cost savings and implementing savings structures.
- Client Service: Service our Client.Monks teams with best in class AI service enablement that allows for continuous growth together. Establish in early kickoff calls whether the client's priority is time or quality before production starts.
- Partnership: Closely collaborate with the Regional business leads to deliver on an end-to-end experience for our clients and structure a model that safeguards the production funnels.
- Cross functional Collaboration: Collaborate closely with growth and account and social monks to identify opportunities and grow together.
- Risk Management: Identify and mitigate potential legal risks and challenges that may impact production timelines, budgets, or quality — including talent likeness, training-data provenance, and model usage rights. Develop and implement contingency plans to ensure smooth project execution and client satisfaction.
- Comms: Roll out & manage yearly comms plan on AI for the studio in collaboration with other leads; comms include social, education, implementation, community or go to monks type of AI related messaging.
- R&D: Develop and manage the regional squad teams to deliver on AI products, help form teams, enable them and hold them accountable to deliver on their commitments.
ESSENTIAL FUNCTIONS
- Executive project / pipeline governance and management across AI film and video productions.
- Oversee, guide and coordinate and deploy new processes and structure as we continue to grow and scale in AI.
- Support sales and lead production strategies to ensure we meet quarterly targets.
- Define and document best practices and contribute to company knowledge sharing effort.
- Collaborate to cross train globally and regionally so workflows never depend on a single person.
JOB DUTIES & RESPONSIBILITIES
- Implementation and deployment of the global vision and delivering of our mission.
- Continuously exploring cutting-edge AI production and operational processes is a must in all work and connecting the Monks ecosystem in all jobs.
- Ensure new business efforts are properly staffed, and the written and oral responses related to Production meet the highest standards.
- Guide and implement AI process and AI products, as well as AI comms and squads.
POSITION REQUIREMENTS
- Bachelor's degree or equivalent experience
- 8–10+ years' experience in motion, film, social, digital and post production / content production, with progressively expanding roles in an advertising agency or high-tech environment.
- Proven experience delivering AI-generated or AI-assisted video content for major brands with strict creative and legal standards.
- Strong leadership, communication, and collaboration skills
- Strong PM Skill Set
- Strong business acumen and problem-solving skills
- Expectation to learn the AI approved tool stacks and dive in head first to be able to build and develop new production and operational processes.
KNOWLEDGE & SKILLS
- Mastery of Motion is required, plus at least one additional discipline area: interactive, emerging media, art buying/print production, programming, or understanding of additional technological related disciplines.
- Hands-on fluency with AI video production pipelines: image-to-video and video generation models (e.g., Kling, Runway, Seedance-class tools), node-based workflows (e.g., ComfyUI), LoRA training and digital-twin approaches, and structured QC/review gates.
- Fluency in complex contracting including talent (union and non union), music licensing/publishing and 3rd party works for hire — including likeness and usage rights in AI contexts.
- Proficiency in Google Suite and Adobe Creative Suite
- Proficiency in the latest AI tools and LLMs and dive in head first to be able to build and develop new processes.
Monks is an equal opportunity employer and is committed to equal opportunity for all employees and applicants. The Company recruits, hires, trains, promotes, compensates, and administers all personnel actions without regard to race, colour, religion, sex, sex stereotyping (including assumptions about a person's appearance or behaviour, gender roles, gender expression, or gender identity), pregnancy (which includes pregnancy, childbirth, and medical conditions related to pregnancy, childbirth, or breastfeeding), gender, gender identity, gender expression, national origin, age, mental or physical disability, ancestry, medical condition, marital status, military or veteran status, citizenship status, sexual orientation, genetic information, or any other status protected by applicable law.
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About Monks
Monks is the global, digital-first, data-driven, unitary operating brand of S4 Capital plc. With a legacy of innovation and specialized expertise, Monks combines an extraordinary range of global Marketing and Technology Services to redefine how brands interact with the world. Through Monks.Flow, its flagship AI ecosystem for marketing orchestration, Monks transforms marketing into a growth engine, collapsing timelines and connecting brands to culture in real time. By deploying bespoke intelligent agents across disciplines and delivering culturally relevant, high-impact creative and digital solutions, Monks solves key critical business challenges across the entire brand enterprise to help brands sustain long-term impact.
Monks was named a Contender in The Forrester Wave™: Global Marketing Services, ranks among Cannes Lions' Top 10 Creative Companies (2022-25) and remains the only partner featured in AdExchanger's Programmatic Power Players list every year (2020-24). Named Adweek's first AI Agency of the Year (2023) and The One Show's inaugural AI Pioneer Organization, Monks was also awarded Business Intelligence Group's 2025 Excellence in Artificial Intelligence Award in both the Organizational and AI Product categories. As a trusted partner to cutting-edge innovators in tech, Monks earned titles such as Optimizely Experimentation Partner of the Year (2025), runner-up for the Adobe Firefly Partner Award (2024), and Workato's AI Visionary Customer Impact Award (2024). Additionally, Monks achieved a record-breaking number of FWAs and continues to hold the most of any partner.
We are an equal-opportunity employer committed to building a respectful and empowering work environment for all people to freely express themselves amongst colleagues who embrace diversity in all respects. Including fresh voices and unique points of view in all aspects of our business not only creates an environment where we can all grow and thrive but also increases our potential to produce work that better represents—and resonates with—the world around us.
Salary Context
This $165K-$180K range is below the median for AI/ML Engineer roles in our dataset (median: $175K across 1356 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 8,943 AI roles we're tracking, AI/ML Engineer positions make up 75% of the market. At Monks, 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 $212,000 based on 11,866 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($172K) sits 19% below the category median. Disclosed range: $165K to $180K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Monks AI Hiring
Monks has 4 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Mexico City, Mexico, New York, NY, US. Compensation range: $180K - $180K.
Location Context
AI roles in New York pay a median of $221,000 across 2,878 tracked positions. That's 4% 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 $253,100 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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