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.

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