Interested in this AI/ML Engineer role at Eurest?
Apply Now →About This Role
Salary: $220,000 - $240,000 / year
Pay Grade: 19
Other Forms of Compensation: Relocation assistance, company vehicle lease/allowance
As the leader in business and industry dining, Eurest is the company to join if you want a rewarding career packed with limitless opportunities. We feed the employees of the nation's largest and most-prestigious companies - in every state and across all industries. As a member of Eurest's leadership and professional support team, you will help our 16,000 chefs, and in-unit associates excel as they deliver world-class meals in corporate cafes and executive dining rooms with on-site catering through vending innovations and more.
Our company is innovative, high performing and fast growing. Our teammates are enthusiastic, committed to quality and thrive on consistently delivering unparalleled results. And did we mention we work with exciting companies and at interesting locations? Come grow your career with Eurest.
Job Summary:
The VPO, Strategic Projects, Engineering, Technology & AI provides executive leadership for the organization's strategic project portfolio, capital projects, architecture and engineering functions, information technology operations, logistics, workplace development, and digital transformation initiatives. This role is responsible for establishing and executing long-term strategies that align physical infrastructure, technology platforms, operational capabilities, and business objectives.
The VPO is a member of the Senior Leadership Team and reports directly to the Senior Vice President. The VPO leads multidisciplinary teams including Project Managers, Engineers, and Technology Professionals to deliver complex programs and enterprise initiatives. This position oversees capital planning, technology modernization, AI integration, workplace infrastructure, and operational improvement efforts while ensuring projects are completed safely, efficiently, on budget, and with measurable business impact.
Key Responsibilities:
Executive Leadership
- Direct and oversee the organization's Project Management Office (PMO), Engineering, Architecture, Capital Projects, Information Technology, and AI modernization functions.
- Establish strategic priorities, annual objectives, and long-term roadmaps supporting organizational growth and operational excellence.
- Lead cross-functional teams responsible for planning, design, implementation, and delivery of enterprise initiatives.
- Serve as a key member of the leadership team, advising executives on infrastructure, technology, operational, and capital investment strategies.
- Develop organizational capabilities that support innovation, scalability, and continuous improvement.
Capital Projects, Architecture & Engineering
- Lead all capital project planning, design, engineering, construction, renovation, and workplace development initiatives.
- Work directly with client and their contracted vendors on projects aligned with Compass scope.
- Direct teams of engineers, architects, project managers, consultants, contractors, and vendors through all phases of project delivery.
- Establish project governance, capital planning standards, engineering practices, and construction management protocols.
- Oversee project budgets, schedules, procurement activities, risk mitigation, and quality assurance.
- Ensure compliance with applicable building codes, safety regulations, environmental standards, and company requirements.
- Develop long-range facility, infrastructure, and workplace modernization strategies.
Information Technology Leadership
- Provide leadership and oversight for all IT operations, infrastructure, systems, applications, cybersecurity, technology support services, and technology investments.
- Establish the organization's technology vision, roadmap, and governance framework.
- Direct enterprise technology implementations, systems integrations, platform enhancements, and modernization initiatives.
- Ensure technology solutions effectively support business operations and strategic objectives.
- Manage IT budgets, technology vendors, service delivery standards, and performance metrics.
- Drive enterprise data management, reporting, and analytics capabilities.
Artificial Intelligence & Automation Strategy
- Lead the development and execution of the organization's AI and automation strategy.
- Identify opportunities to leverage AI, machine learning, generative AI, and automation technologies to improve productivity, efficiency, customer experience, and decision-making.
- Establish AI governance, risk management, security, compliance, and responsible-use standards.
- Oversee the implementation and scaling of AI-enabled solutions across business functions.
- Evaluate emerging technologies and identify opportunities to enhance organizational competitiveness and innovation.
Project Management & Strategic Initiatives
- Lead a portfolio of high-impact strategic projects across operations, technology, facilities, engineering, and business transformation.
- Establish project management methodologies, governance standards, reporting structures, and performance metrics.
- Ensure effective prioritization, resource allocation, and project execution.
- Monitor progress against milestones, budgets, timelines, and business objectives.
- Communicate project performance, risks, and strategic recommendations to executive leadership.
Financial & Resource Management
- Develop and manage operating and capital budgets across multiple functional areas.
- Evaluate investment opportunities through ROI analysis, business cases, and strategic planning.
- Ensure responsible stewardship of organizational resources and capital investments.
- Forecast resource requirements and align staffing strategies with business priorities.
People Leadership
- Lead, mentor, and develop teams of Project Managers, Engineers, Architects, Technology Professionals, Analysts, and Logistics personnel.
- Establish performance standards and accountability measures that drive execution and results.
- Foster a culture of innovation, collaboration, continuous improvement, and operational excellence.
- Build succession plans and organizational capabilities that support future growth.
Qualifications:
Education & Experience
- Bachelor's Degree in Engineering, Architecture, Construction Management, Information Technology, Business Administration, Project Management, or related field required.
- Master's Degree, MBA, Engineering Management, or related advanced degree preferred.
- Minimum 10 years of progressive leadership experience overseeing large-scale projects, engineering functions, technology operations, and business transformation initiatives.
- Minimum 7 years of experience leading managers, project teams, engineers, and technical professionals.
- Demonstrated experience managing capital project portfolios, technology organizations, and enterprise-wide strategic initiatives.
Technical Knowledge
- Strong knowledge of capital project management, engineering, architecture, construction management, and workplace infrastructure.
- Executive-level experience overseeing commercial kitchen construction, renovation, and capital improvement initiatives, with a strong understanding of applicable regulatory requirements, certifications, and industry standards preferred.
- Advanced understanding of IT operations, enterprise systems, cybersecurity, technology modernization, and digital transformation.
- Experience implementing AI, automation, analytics, and emerging technology solutions.
- Knowledge of project portfolio management, change management, and organizational transformation methodologies.
- Understanding of procurement, supply chain, logistics, and operational excellence principles.
Leadership Competencies
- Executive presence with the ability to influence and drive enterprise-wide initiatives.
- Exceptional strategic planning and business acumen.
- Strong financial management and budgeting expertise.
- Proven ability to lead complex, multidisciplinary teams.
- Outstanding written, verbal, presentation, and stakeholder management skills.
- Demonstrated success delivering large-scale capital, technology, and operational projects.
Apply to Eurest today!
Eurest is a member of Compass Group USA
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Associates at Eurest are offered many fantastic benefits.
- Medical
- Dental
- Vision
- Life Insurance/ AD
- Disability Insurance
- Retirement Plan
- Paid Time Off
- Holiday Time Off (varies by site/state)
- Associate Shopping Program
- Health and Wellness Programs
- Discount Marketplace
- Identity Theft Protection
- Pet Insurance
- Commuter Benefits
- Employee Assistance Program
- Flexible Spending Accounts (FSAs)
- Paid Parental Leave
- Personal Leave
Associates may also be eligible for paid and/or unpaid time off benefits in accordance with applicable federal, state, and local laws. For positions in Washington State, Maryland, or to be performed Remotely, click here or copy/paste the link below for paid time off benefits information.
https://www.compass-usa.com/wp-content/uploads/2026/01/2026_Wage-Transparency_Eurest.pdf
Compass Group is an equal opportunity employer. At Compass, we are committed to treating all Applicants and Associates fairly based on their abilities, achievements, and experience without regard to race, national origin, sex, age, disability, veteran status, sexual orientation, gender identity, or any other classification protected by law.
Qualified candidates must be able to perform the essential functions of this position satisfactorily with or without a reasonable accommodation. Disclaimer: this job post is not necessarily an exhaustive list of all essential responsibilities, skills, tasks, or requirements associated with this position. While this is intended to be an accurate reflection of the position posted, the Company reserves the right to modify or change the essential functions of the job based on business necessity. We will consider for employment all qualified applicants, including those with a criminal history (including relevant driving history), in a manner consistent with all applicable federal, state, and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, and the New York Fair Chance Act.
Eurest maintains a drug-free workplace.
Applications are accepted on an ongoing basis.
Salary Context
This $220K-$240K range is above the 75th percentile 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 Eurest, 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 11,866 positions with disclosed compensation. This role's midpoint ($230K) sits 8% above the category median. Disclosed range: $220K to $240K.
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.
Eurest AI Hiring
Eurest has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Redmond, WA, US. Compensation range: $240K - $240K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 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 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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