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Location: Palo Alto Other locations: Primary Location Only Salary: Competitive Date: Oct 1, 2026 Job description
Requisition ID: 1745232 At EY, we’re all in to shape your future with confidence.
We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
The Opportunity
EY is scaling Physical AI capabilities in California (Palo Alto) to serve as a premier engagement hub for clients, industry leaders, startup founders, alliance partners, investors, and the broader innovation ecosystem.
We are seeking a highly organized, client-centric, and operationally driven Assistant Director to serve as the Client Activation Manager for EY.ai Labs (Palo Alto). This role will be responsible for ensuring every client engagement is delivered with excellence, from pre-visit preparation and technical showcase readiness through onsite experience management and post-engagement coordination.
The Client Activation Manager will work closely with Experience Lead- EY.ai Labs (Palo Alto), the EY Physical AI leadership, client account teams and alliance partners to create memorable, customized, and business-relevant experiences for executives, innovation leaders, and strategic stakeholders. The role requires a unique combination of client engagement expertise, operational discipline, technology curiosity, project management capability, and cross-functional collaboration.
The ideal candidate excels in managing complex stakeholder environments, coordinating technical and non-technical teams, orchestrating executive experiences, and ensuring seamless delivery of innovation-focused engagements.
Key Responsibilities
In this role, you will be responsible for the planning, activation and success of the Palo Alto Physical AI Lab. Your key responsibilities will include:
- Lead end-to-end planning and activation of client visits, executive briefings, innovation workshops, industry sessions, and Physical AI showcase experiences.
- Partner with account teams and engagement leaders to understand client objectives, industry context, business priorities, and desired outcomes for each lab visit.
- Coordinate setup, testing, and validation of demonstrations involving Physical AI technologies prior to client engagements, as well as coordinate the customization of demonstrations, showcases, presentations, and experience journeys to ensure relevance and impact for each audience.
- Maintain readiness of demonstration assets from labs or ecosystem partners, executive briefing materials, industry use cases, videos, prototypes, and showcase environments to support client engagements.
- Serve as the primary coordination point between the Palo Alto lab and Physical AI engineering and R&D teams [including the EY.ai Labs team (Alpharetta)], to ensure timely content updates, showcase enhancements, and technology refreshes.
- Manage the experience flow during client visits, ensuring seamless coordination across presenters, demonstrations, technical teams, executives, and supporting staff.
- Oversee day-to-day lab operations including showcase scheduling, asset tracking, facility readiness, visitor logistics, operational processes, and engagement support.
- Establish operational processes, playbooks, and governance practices to ensure consistent delivery of high-quality client experiences. Also, capture and document client feedback, engagement outcomes, operational insights, and improvement opportunities to continuously enhance the lab experience.
- Collaborate with Branding/marketing teams and leadership teams to support executive events, workshops, ecosystem engagements, and strategic visits hosted at the lab.
- Coordinate knowledge sharing and best-practice exchange across the broader EY Physical AI lab network and contribute to continuous experience innovation.
- Support the rollout of new demonstrations, industry-specific showcases, and emerging Physical AI capabilities in alignment with EY commercialization priorities.
Skills and Attributes for Success
To excel in this role, you will need a blend of operational excellence, ecosystem leadership, business storytelling and innovation mindset, as well as strong interpersonal skills and the ability to coordinate between technical and business teams. Key attributes include:
- Strong program and project management skills with the ability to manage multiple high-visibility engagements simultaneously.
- Strong stakeholder management skills and ability to coordinate across leadership teams, account teams, engineers, researchers, and external partners.
- Excellent communication, facilitation, and executive presence to deliver executive experience.
- Ability to translate technical concepts into business-relevant client experiences and engagement journeys.
- Strong organizational and execution skills with a proactive, problem-solving mindset.
- High level understanding of emerging technologies including AI, robotics, automation, digital twins, simulation, and intelligent systems.
- Ability to operate effectively within fast-paced, evolving, and highly collaborative environments.
- Strong customer-service orientation with a focus on delivering exceptional client outcomes and experiences.
Preferred Skillsets:
- MBA or advanced degree in Business, Engineering, Technology, Innovation Management, Marketing, Communications, or a related field.
- Experience working within a Big Four, Tier 1 consulting firm, technology company, innovation lab, venture ecosystem, accelerator, or startup environment.
- Prior experience managing innovation centers, executive briefing programs, customer experience centers, demonstration facilities, or similar engagement environments is a plus.
- Existing network across Silicon Valley, Bay Area innovation communities, startups, venture capital firms, and technology ecosystems.
- High level familiarity with Physical AI, robotics platforms, autonomous systems, digital twins, simulation technologies, or AI-enabled industrial solutions. Technical experience would be a bonus.
What we offer you
The compensation ranges below are provided in order to comply with United States pay transparency laws. Other geographies will follow their local salary guidelines, which may not be a direct conversion of published US salary ranges. At EY, we harness our collective strength to empower you to shape your future with confidence through professional growth, personal fulfillment and an inclusive culture. Learn more at ey.com/us/careers.
- We offer a comprehensive compensation and benefits package where you’ll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job is:
- + New York City, Boston, and Washington DC Metro Areas, Washington State, and Southern California offices – $112,000 to $190,400 + Bay Area California offices – $116,700 to $198,300 + All other offices locations in the US, including Sacramento – $93,300 to $174,500
- Individual salaries within these ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.
- Under our flexible vacation policy, you’ll decide how much vacation time you need based on your own personal circumstances. You’ll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.
Are you ready to shape your future with confidence? Apply today.
- To make the most of your application experience, please limit yourself to two applications within a six-month period.
- EY accepts applications for this position on an on-going basis.
- For those living in California, please click here for additional information.
- At EY, our values set the foundation for how we work and the behaviors we expect of our people. Any misrepresentation or falsification of information or lack of integrity at any point in the recruiting process may result in withdrawal of your candidacy, revocation of an offer or immediate termination of employment.
EY | Building a better working world
EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.
Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.
EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
All in to shape the future with confidence.
EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law.
EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1-800-EY-HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY’s Talent Shared Services Team (TSS) or email the TSS at [email protected].
Salary Context
This $112K-$198K range is below the median for AI/ML Engineer roles in our dataset (median: $176K across 1540 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 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At EY, 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 $212,000 based on 11,857 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($155K) sits 27% below the category median. Disclosed range: $112K to $198K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. 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: $272,275; VP: $235,000.
EY AI Hiring
EY has 65 open AI roles right now. They're hiring across AI/ML Engineer, Data Engineer, AI Engineering Manager, AI Architect. Positions span Secaucus, NJ, Sydney, New South Wales, Australia, McLean, VA, US. Compensation range: $142K - $357K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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