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Senior Machine Learning Engineer - AMP

Fulltime AI
Beirut, Lebanon
Full-time
AI tools:
Anthropic
OpenAI
You apply on Fulltime AI's own careers site

You’ll build and ship AI features for a hospitality pricing product, from forecasting and rate recommendations to the services and interfaces revenue managers use. The role also covers data pipelines, LLM-driven features, and model evaluation and monitoring.

Full-time
On-site
3–5 years

Skills & Expertise

Python
TypeScript
JavaScript
SQL
LLM APIs
time-series forecasting
cloud deployment
CI/CD

Key Responsibilities

Build forecasting, rate-recommendation, and LLM features for hotel revenue management.

Develop pipelines that turn competitor-rate data into reliable model inputs.

Create evaluation, monitoring, APIs, and user interfaces for production AI features.

Full Description

Aspire Software is looking for a Senior Machine Learning Engineer to join our team in Lebanon.

Here is a little window into our company: Aspire Software operates and manages wholly owned software companies, providing mission-critical solutions across multiple verticals. By implementing industry best practices, Aspire delivers a time sensitive integration process, and the operation of a decentralized model has allowed it to become a hub for creating rapid growth by reinvesting in its portfolio.

About the job:

You will build AI features end to end: the model or pipeline that produces the decision, the service that runs it, and the product surface where a revenue manager sees and acts on it. This is not a research role and it is not a pure app-dev role — it is the bridge between them.

Examples of what you'd own in your first year:

• Forecasting and rate-recommendation logic that feeds our auto-publish engine, including the guardrails that keep recommendations inside a property's tolerance LLM-driven features: natural-language explanations of why a rate moved, conversational querying of a property's performance, automated market commentary

• Rate-intelligence pipelines — ingesting competitor rates, cleaning messy third-party data, and turning it into signals the model can trust

• Evaluation harnesses and monitoring so we know when a model degrades before a customer does

• The full-stack surface around all of the above: APIs, data models, and the UI that exposes them

Requirements

• 3–5 years building and shipping production software, with meaningful AI/ML work in that time

• Strong Python; comfortable in TypeScript/JavaScript for the application layer

• Hands-on experience with LLM APIs (Anthropic, OpenAI or similar) — prompt design, structured

• output, tool use, retrieval, and the evaluation discipline to know whether any of it is working

• Solid SQL and data modeling; you can reason about a schema and write queries that don't melt the database

• Experience with at least one of: time-series forecasting, pricing/optimization models, or recommendation systems

• Comfort with messy, incomplete, real-world data — third-party feeds, inconsistent APIs, partial history

• Cloud deployment experience and familiarity with modern CI/CD

Nice To Have:

• Hospitality, travel, pricing, or marketplace domain experience

• Experience integrating with PMS, channel manager, or booking-engine APIs

• Background in a small startup where you owned a system rather than a ticket queue

How we work, and who succeeds here

• We hire for ownership as much as for stack. The engineers who do well:

• Take technical ownership. You're handed a problem, not a spec. You decide what to build, flag the trade-offs, and are accountable for the result in production — including when it breaks at an inconvenient hour.

• Are intrinsically driven. Nobody will watch your calendar. You choose the right next thing to work on when the direction is ambiguous, and you finish things.

• Communicate well asynchronously. Written updates that a busy reader can act on. You surface blockers early rather than going quiet. Clear, complete PR descriptions and issue comments.

• Manage your own time zone. You're responsible for maintaining reliable overlap with the team and for being predictable about when you're reachable.

Applications are handled on Fulltime AI's site