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About This Role
About API
Accommodations Plus International (API) is the global leader in crew accommodation and travel logistics, powering over 18 million crew room nights each year for 100\+ airlines and travel operators worldwide. Our Global reach ensures that airline crews are rested, transported, and connected so global aviation runs on time.
Position Overview:
The AI Strategy Analyst owns the operational backbone of API’s AI Enablement program — the cross\-functional cadence, experimentation discipline, adoption measurement, and vendor management that turn AI investment into measurable productivity and operating leverage. The role also has responsibility within the Strategy function to drive alignment and execution on strategic initiatives across the organization, including corporate development and inorganic growth activities. This is a remote position.
Success in this Role* Milestone: drive Claude Enterprise adoption and rollout; own AI Sandbox rollout and cross\-functional use\-case identification and development, including both internal and external (customer\-facing) applications.
- Long\-term contributions: drive API toward an AI\-native end\-state through leadership, training, and execution.
- Mastery: Claude as a daily working tool; development of AI\-enabled processes and outcomes across internal operations and customer\-facing applications.
- Impact: drive quantifiable ROI through dollar savings, efficiency generation, and AI productization and monetization.
- Engagement: direct engagement with the CSO and EVP of Strategy \& Innovation; broad engagement opportunity across the organization and with external parties including investors, vendors, partners, and acquisition targets.
What You’ll Do
Essential Functions: *Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.*
Key responsibilities* Experimentation portfolio — Run intake, hypothesis design, metric definition, and outcome documentation for AI experiments across Engineering, Client Delivery, and Corporate functions. Drive go/no\-go reviews and graduation\-to\-production decisions.
- Pilot management — Run end\-to\-end management of AI pilots across the portfolio. Own validation evidence, vendor coordination, integration readiness, and graduation decisions.
- Adoption and management — Partner to drive org\-wide training, communications, and enablement for Claude Enterprise and Microsoft Copilot. Move seat utilization from license to behavior. Produce the monthly AI scorecard: experiments launched, seats utilized, automation rates, FTE\-equivalent savings, and experiments graduated.
- Sandbox operations — Co\-lead AI sandbox management with Engineering. Manage onboarding from initial cohort through expansion, including use\-case intake, prioritization, and graduation criteria.
- Internal AI optimization — Work with IT and internal stakeholders to manage, analyze, and optimize internal utilization of AI across the organization — identifying gaps, surfacing high\-value use cases, and improving return on AI spend.
- Vendor and budget management — Own day\-to\-day relationship management for AI tooling vendors and the sandbox platform. Track spend against the approved Opex plan and flag variances.
- Strategy execution — Drive alignment and execution on strategic initiatives across the organization. Support corporate development and inorganic growth activities, board and investor materials, VCP reporting, and ad hoc strategic projects on the CSO’s agenda.
What You’ll Bring
Minimum Qualifications* Must have working personal fluency with Claude (mandatory) and other enterprise AI tooling (Microsoft Copilot or equivalent); demonstrated ability to design and document hypothesis\-driven experiments.
- 2–5 years of professional experience in program management, strategy operations, consulting, private equity, or transformation roles, with demonstrated experience running cross\-functional projects to measurable outcomes.
- Strong written communication; ability to produce CEO\- and board\-quality artifacts.
- Comfort operating in ambiguity within a small, fast\-moving team.
Preferred Qualifications* Technical background (educational or professional) — computer science, engineering, data, or comparable hands\-on experience with software, automation, or AI systems.
- Exposure to voice AI, document automation, or contact\-center modernization.
- Prior experience in a PE\-portfolio company or other high\-growth, lean environment.
Education
Bachelor’s degree required. Technical or quantitative field (computer science, engineering, economics, mathematics, data science) preferred. Advanced degree welcome but not required.
Position Type and Expected Hours of Work
Full time, Monday through Friday, normal core business hours and as needed on nights and weekends unless otherwise specified.
Supervisory Responsibility
Individual contributor role. No direct reports at hire. May supervise contractors, vendors, or interns supporting AI Enablement initiatives.
Travel Requirements
Occasional travel to API headquarters in Melville, NY and to vendor or partner sites, estimated at less than 10% of working time.
What’s In it for You* Health, dental, and vision insurance
- Competitive 401(k) matching
- Paid Time Off
- AI mastery and hands\-on building with frontier AI tools
- AI Enablement skillset and experience across an enterprise rollout
- Program management experience on a high\-visibility, board\-tracked initiative
- High\-growth company environment backed by private equity
- High autonomy and entrepreneurial role with direct CSO and EVP engagement
Compensation
Compensation is determined based on several factors, including the candidate’s experience, qualifications, skill set, and location, as well as internal equity and external market benchmarks.
A good faith annual salary range for this position is $130,000 to $150,000, plus a discretionary 10% bonus.Who We Are
API is the global leader for crew accommodation solutions, and we are changing the way businesses manage travel. Our technology platform streamlines the entire crew planning process, making day\-to\-day operations more efficient and elevating the crew layover experience. API’s proprietary technology, mobile solutions and our experienced team are positioned to offer our clients a complete, end\-to\-end platform that integrates seamlessly into their process. We are looking for dynamic, creative, and tech savvy individuals to join our team. If you are passionate about hard work, providing impeccable service, technology, and solutions to our clients then API may be a great fit for you!
Other Duties
Duties, responsibilities and activities may change at any time according to business needs.
The performance of additional responsibilities if you are designated as a Data Protection Champion (DPC), Senior Information Risk Owner (SIRO) or Information Assurance Accounting Officer (IAAO).
Work Environment
This position operates in a professional office environment. This role routinely uses standard office equipment such as computers, phones, photocopiers, filing cabinets and fax machines.
Physical Demands
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is regularly required to talk or hear. The employee frequently is required to stand, walk; use hands to finger, handle or feel; and reach with hands and arms.
AAP/EEO Statement
Accommodations Plus International is an Equal Opportunity Employer that does not discriminate on the basis of actual or perceived race, creed, color, religion, alienage or national origin, ancestry, citizenship status, age, disability or handicap, sex, marital status, veteran status, sexual orientation, genetic information, arrest record, or any other characteristic protected by applicable federal, state or local laws. Our management team is dedicated to this policy with respect to recruitment, hiring, placement, promotion, transfer, training, compensation, benefits, employee activities and general treatment during employment.
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Salary Context
This $130K-$150K range is below 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 Accommodations Plus International, 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 $181,170 based on 12,692 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($140K) sits 23% below the category median. Disclosed range: $130K to $150K.
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.
Accommodations Plus International AI Hiring
Accommodations Plus International has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $150K - $150K.
Remote Work Context
Remote AI roles pay a median of $170,000 across 1,926 positions. About 15% of all AI roles offer remote work.
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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