AI Engineer
- Location
- US
- Workplace
- Remote
- Employment
- Full Time
- Salary
- USD 190,000–200,000/yr
Posted 24d ago
Job Information
AI Engineer Job
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Title
AI Engineer
EOE Statement
We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status or any other characteristic protected by law.
Description
Job Title
AI Engineer
Location
New York, NY
Department
Technology/Revenue Strategy
Reports To
Chief Executive Officer
FLSA Status
Exempt
Work Type
Remote Position with occasional travel to the Corporate Office
Employment Type
Full Time
Company
Rebel Hotel Company
About Rebel Hotel Company
Rebel Hotel Company is one of the fastest-growing third-party hotel management companies in the United States, recognized for delivering bold results, operational excellence, and distinctive guest experiences. We operate a diverse portfolio of full-service, lifestyle, and branded hotels across major metropolitan and resort markets. We are building a culture of leadership, innovation, and accountability—and we’re just getting started.
Position Summary
We're a hospitality company building the next generation of intelligent pricing, demand, and guest-experience systems. Today our commercial teams run rate strategy, RFP negotiations, and account planning on spreadsheets and intuition. We're hiring an AI Engineer to turn that work into software — models and tools that forecast demand, optimize rates, and surface account intelligence so our revenue managers make sharper decisions, faster.
This is a hands-on engineering role with direct line of sight to revenue. You'll work alongside revenue managers, sales leaders, and data analysts, shipping production systems that touch real pricing and booking decisions across our portfolio.
What You'll Build
- Demand forecasting models that predict occupancy and room-night demand by property, segment, day-of-week, and season — accounting for events, seasonality, and booking pace.
- Dynamic pricing and rate-optimization engines that recommend BAR and corporate rates, balancing occupancy, ADR, and RevPAR against competitor positioning.
- Account intelligence tooling that ingests internal production data and external signals (M&A activity, headcount trends, travel-budget shifts) to flag growing accounts, at-risk accounts, and uncaptured market opportunity.
- Labor and staffing models that forecast labor demand against projected occupancy and arrivals — optimizing schedules, hours, and cost across housekeeping, front desk, F&B, and other departments while protecting service levels.
- RFP and negotiation support tools that help the team price contracts, model rate scenarios, and prioritize target accounts during RFP season.
- LLM-powered workflows — summarizing market intelligence, drafting account strategy notes, and answering natural-language questions over revenue data.
- A testing laboratory for beta technologies — stand up and run a controlled environment where new AI tools and models can be piloted, stress-tested, and validated against real operational data before broader rollout, including the experimentation framework, sandboxed data, and feedback loops with property and commercial teams
What You'll Do
- Design, train, evaluate, and deploy machine learning models on real booking, rate, and market data.
- Build data pipelines that bring together PMS, CRS, booking-channel, and third-party market data into clean, reliable feature sets.
- Stand up the infrastructure to serve models in production — APIs, monitoring, retraining, and guardrails.
- Operate the beta testing lab — design pilots, recruit internal users, measure results, and decide what graduates to production versus what gets killed.
- Partner closely with revenue and commercial teams to translate domain knowledge into product, and to make sure outputs are trustworthy and actionable.
- Define and track the metrics that matter — forecast accuracy, recommendation adoption, labor cost and productivity, and downstream revenue impact.
What We’re Looking For
Required
- 3+ years building and shipping ML systems in production (not just notebooks).
- Strong Python and the modern ML/data stack (e.g. pandas, scikit-learn, PyTorch or TensorFlow, SQL).
- Solid grounding in forecasting, optimization, or recommendation/pricing problems.
- Experience taking models from prototype to deployed service, including monitoring and iteration.
- Ability to communicate clearly with non-technical stakeholders and translate business problems into technical ones.
Nice to have
- Experience in hospitality, travel, airlines, retail, or another revenue-management-driven industry.
- Familiarity with dynamic pricing, demand modeling, or yield/revenue management.
- Experience integrating LLMs into applications (RAG, structured extraction, agentic workflows).
- Cloud and MLOps experience (AWS/GCP/Azure, containerization, CI/CD for ML).
- Comfort with experimentation and causal measurement (A/B testing, uplift modeling).
What We Offer
- Competitive base salary and performance-based incentive plan
- Medical, dental, and vision insurance
- 401(k) plan with company match
- Paid time off and holidays
- Career advancement opportunities within a rapidly growing company
- A chance to be part of the Rebel movement redefining hospitality leadership
Why This Role
You'll own meaningful problems end-to-end, see your work move real revenue, and help build a data and AI capability from an early stage. If you want your models to ship and matter rather than sit in a backlog, this is that role.
Salary Range
$190,000 - $200,000 annually
At Rebel Hotel Company, we don’t manage hotels the old way—we challenge the status quo. If you’re ready to lead with vision, act with ownership, and make your mark in the hospitality world, we want to meet you.
Full-Time/Part-Time
Full-Time
Salary Range
$190,000 - $200,000 annually
Exempt/Non-Exempt
Exempt
This position is currently accepting applications.
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Skills
- Python
- pandas
- scikit-learn
- PyTorch
- TensorFlow
- SQL
- LLM
- RAG
- AWS
- GCP
- Azure
- containerization
- CI/CD
- A/B testing
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