AI-ML Engineer developing machine learning models for hotel revenue optimization at Ampliphi. Working on pricing algorithms and data pipelines in a hybrid work model.
Responsibilities
Massively improve and extend our multi-factor pricing algorithms (occupancy deviation, pickup velocity, price elasticity, booking curve forecasting, seasonality detection) by leveraging machine learning and mathematical optimization
Scraping, ingesting, processing, storing, and integrating data with PMS systems for dynamic pricing and decision-making
Build API endpoints (FastAPI) and frontend components (React/TypeScript) for revenue managers to interact with pricing strategies, overrides, and analytics
Contribute to our AWS architecture (ECS Fargate, SQS, EventBridge, S3, CloudWatch) and help scale the platform as we grow
Requirements
3+ years of professional machine learning and software development experience, with a strong background in both backend and frontend engineering
Proven expertise in Python development, including async programming, ORMs, and building production-level APIs
Hands-on experience with machine learning, including model development, training, and integration into production systems
In-depth understanding and experience applying mathematical optimization techniques, particularly in the context of dynamic pricing and revenue management, within the hospitality industry
Experience with algorithm development for complex pricing models (e.g., occupancy deviation, booking velocity, seasonality detection) and predictive analytics
Familiarity with large language models (LLMs) like OpenAI, Anthropic, and frameworks such as LangChain or LangGraph to build agentic workflows
Strong proficiency in React and TypeScript for building intuitive user-facing features
AI-assisted development tools are a must, use of tools like Claude Code, GitHub Copilot, or Cursor to streamline development and enhance productivity
Proficiency with relational databases, including SQL (PostgreSQL preferred), and solid data modeling skills
Experience with AWS cloud services or equivalent cloud platforms and a strong understanding of modern cloud infrastructure
Comfortable working with Docker, CI/CD pipelines, and managing production deployments
Fluent in English, both written and verbal, is essential
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