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Job Description:
The Marketplace \& Partnerships division is responsible for all elements of strategic partnerships for the dentsu Media practice in the US. The team sits at the intersection of dentsu’s media agencies (Carat, iProspect and dentsuX), clients, investment and activation communities, and Amplifi, the commercial innovation arm for dentsu. The team is responsible for translating the business needs of dentsu’s clients, the strategic and commercial imperatives of dentsu itself, as well as emergent and established trends across the industry and society into strategic, value\-driven, and beneficial partnerships. They also set the strategic agenda for partnerships at dentsu in the marketplace, how that pertains to new business and in product/solution design within dentsu.
This VP role focuses on the rapidly evolving landscape of Large Language Models (LLMs), generative AI platforms, and model infrastructure. Sitting at the intersection of enterprise AI strategy, product innovation, engineering, and commercial operations, this role ensures that the organization has the right LLM partners, capabilities, and commercial agreements to accelerate growth and deliver differentiated value for clients.
The VP will operate as an enterprise subject matter expert in LLMs—including foundation models, finetuning partners, vector database vendors, model ops platforms, and safety/guardrail technologies. They will define our LLM partnership strategy, negotiate and structure commercial and technical agreements, and ensure that these partnerships align with the strategic, innovative, and value driven objectives of the organization. The VP will contribute meaningfully to the broader AI partnership vision across all channels and business units. Reporting into the SVP, Commerce \& Intent Partnerships Lead, this role will be tasked with contributing their core objectives towards the overall partnership strategy and vision across all channels.‑matter expert in LLMs—including foundation models, fine‑tuning partners, vector database vendors, model‑ops platforms, and safety/guardrail technologies. They will define our LLM partnership strategy, negotiate and structure commercial and technical agreements, and ensure that these partnerships align with the strategic, innovative, and value‑driven objectives of the organization. The VP will contribute meaningfully to the broader AI partnership vision across all channels and business units.
Given the cross‑functional nature of AI transformation, this role will collaborate with product, engineering, data science, legal, security, media, and commercial teams to create mutually beneficial outcomes. The VP will also provide senior leadership with insights on market evolution, emerging risks, competitive differentiation, and partnership performance.
Key Responsibilities
- Own and lead a portfolio of LLM focused partnerships, including model providers, infrastructure platforms, safety/guardrail vendors, and model ops technologies.‑focused partnerships, including model providers, infrastructure platforms, safety/guardrail vendors, and model‑ops technologies.
- Translate market intelligence, client needs, and internal priorities into a comprehensive annual LLM partnership strategy.
- Identify, vet, and cultivate new LLM and gen‑AI partnership opportunities that enhance product innovation and enterprise capabilities.
- Serve as a senior subject‑matter expert on LLM technologies, while representing adjacent AI domains in partnership conversations.
- Collaborate with Product, Engineering, and Data Science to ensure LLM partnerships align with capability roadmaps, model requirements, and value‑creation goals.
- Work cross‑functionally across AI, media, creative, and commercial teams to design integrated go\-to\-market strategies leveraging LLM partners.
- Evaluate commercial viability and technical compatibility of LLM opportunities; ensure each partnership is optimized for performance, safety, and cost efficiency.
- Act as a problem solver and integrator, coordinating multiple stakeholders and maintaining forward momentum across complex partnership initiatives.
- Drive excellence in LLM partnership governance, reporting, compliance, and enablement across the organization.
- Represent the organization as an AI thought leader in market‑facing opportunities (panels, PR, partner events) within the LLM domain.
- Provide communication, documentation, and knowledge management for all LLM partnerships, ensuring transparency, alignment, and adoption across teams.
- Support client conversations and new‑business pitches as the LLM expert and AI partnership lead.
- Liaise and partner with Product and Solutions organizations to facilitate partnership development and capability creation within dentsu.
- Consult on client business to build custom partnership plans and subject\-matter expertise of partner landscape.
We are looking for candidates who can deliver sustainable change, think strategically, and retain focus in a fast\-changing environment. The ideal candidate brings rigor to a multi\-disciplinary business with many stakeholders. Here are some key characteristics of a successful candidate:
- You possess strategic thinking and the ability to make critical business decisions aligned with organizational goals.
- You challenge status quo and inspire new ideas and approaches.
- You have experience in organizational transformation and leading large\-scale change management programs.
- You are comfortable working with multiple senior peers and stakeholders, taking initiative and ownership.
- Business acumen, client\-centricity, and a commercial mindset are essential, along with a genuine passion for people.
- Balance, prioritize and properly assign work associated with multiple, concurrent projects and stakeholders
Qualifications:
- 10\+ years’ experience within the digital industry as a partnership or investment lead at a reputable agency or partner.
- 5\+ years’ experience management of a team – with the ability to lead a highly successful team.
- Consistent exceptional project management, ability to prioritize and meet deadlines.
- Excellent verbal and written communications, presentation, and analytical skills; must be comfortable working with and presenting sophisticated metrics to C\-level.
- Ability to retain professionalism in all situations.
- Passion for problem\-solving and collaboration across teams.
- Ability to translate complex ideas into actionable solutions.
The annual salary range for this position is 165K\- 175K. Placement within the salary range is based on a variety of factors, including relevant experience, knowledge, skills, and other factors permitted by law.
Benefits available with this position include:
- Medical, vision, and dental insurance,
- Life insurance,
- Short\-term and long\-term disability insurance,
- 401k,
- Flexible paid time off,
- At least 15 paid holidays per year,
- Paid sick and safe leave, and
- Paid parental leave.
Dentsu also complies with applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, in accordance with its plans and policies. For further details regarding Dentsu benefits, please visit www.dentsubenefitsplus.com.
To begin the application process, please click on the “Apply” button at the top of this job posting. Applications will be reviewed on an ongoing basis, and qualified candidates will be contacted for next steps.
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Location:
New YorkBrand:
AmplifiTime Type:
Full timeContract Type:
Permanent
Dentsu is committed to providing equal employment opportunities to all applicants and employees. We do this without regard to race, color, national origin, sex , sexual orientation, gender identity, age, pregnancy, childbirth or related medical conditions, ancestry, physical or mental disability, marital status, political affiliation, religious practices and observances, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law.
Dentsu is committed to providing reasonable accommodation to, among others, individuals with disabilities and disabled veterans. If you need an accommodation because of a disability to search and apply for a career opportunity with us, please send an e\-mail to [email protected] by clicking on the link to let us know the nature of your accommodation request and your contact information. We are here to support you.
Salary Context
This $165K-$175K range is below 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 Dentsu, 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. This role's midpoint ($170K) sits 21% below the category median. Disclosed range: $165K to $175K.
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.
Dentsu AI Hiring
Dentsu has 3 open AI roles right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $125K - $175K.
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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