Machine Learning Engineer

Summary

Andersen is seeking a Machine Learning Engineer for a project developing intelligent travel technology solutions and enhancing large-scale digital platforms with AI-driven capabilities.

The customer is a technology-driven company in the travel sector, providing a comprehensive booking and procurement platform for industry professionals. Its solutions support large transaction volumes, integrate with a wide network of partners, and offer tools that streamline operations and enhance productivity. Focused on innovation and scalability, the customer continues to expand its ecosystem, strengthen partnerships, and improve data accuracy to deliver a modern digital infrastructure for the travel value chain.

The project is focused on developing and enhancing a travel technology platform that connects travel agencies and tour operators with a global network of suppliers. It enables real-time access to travel products and services, supporting large-scale transaction processing, booking operations, and seamless travel distribution.

Responsibilities

• Owning the end-to-end ML component of the agent-lead scoring system: design, build, deploy and iterate on a model that re-ranks agents to improve the close rate while respecting fairness, sales targets, capacity constraints and revenue potential.
• Building and maintaining data and feature pipelines — ingesting data from the Azure Fabric lakehouse / SQL sources, extracting and engineering features for agents, leads and their interactions, and orchestrating the flow (e.g. Airflow).
• Developing and benchmark tabular ML models (baseline logistic regression through gradient-boosting models), selecting and justifying the approach and the right evaluation metrics for the business objective.
• Designing and runing experiments and A/B tests in production to measure whether the model improves performance against the current rules-based scoring, addressing cold-start and normalisation so new agents and leads are scored fairly.
• Exposing the model as a service/API so backend applications can integrate it into the live scoring flow, and deploy it on Azure (or comparable infrastructure) with scheduled (likely weekly) retraining.
• Setting up monitoring and retraining to track model performance over time and decide when re-training or model changes are warranted.
• Collaborating with backend developers, the data analytics team and an intern — gathering domain knowledge, identifying where features and data points live, specifying additional data to capture, and upskilling the wider team on ML.
• Challenging stakeholders constructively and justify ML decisions with evidence, including defending the value of a dedicated ML model over ad-hoc LLM usage, and explain the system clearly to non-ML colleagues.

Requirements

• Strong hands-on in classic/tabular ML (logistic regression, gradient boosting: XGBoost / LightGBM / CatBoost, random forests) plus sound choice of evaluation metrics for 5+ years.
• Strong Python and the ML/data stack (Pandas, Polars, scikit-learn; PySpark/Dask).
• Experience exposing models as services/APIs (FastAPI) for other applications to integrate.
• Data engineering: ingestion, feature-extraction and orchestration pipelines (Airflow), SQL + data lakehouse.
• Taking a model from PoC to production (containerisation, scheduled retraining).
• Experiment design, offline evaluation and A/B testing in production.
• Level of English – from Upper-Intermediate and above.

Desired skills

• Experience in travel domain.
• Certificates.

Reasons to join us

• Andersen cooperates with such companies as Siemens, Johnson & Johnson, AstraZeneca, BNP Paribas, Allianz, Ryanair, TUI, Verivox, Media Markt, etc..
• For the past four years, our company has been growing annually by 60–100%, and we constantly involve top-notch specialists in our team.
• Andersen has mentoring and adaptation systems for new employees, and transparent performance review and assessment systems will allow you to determine your development path and plan your growth.
• The most important thing that we value in our employees is a commitment to continuous learning. The company supports them in this and gives them access to the best educational platforms, seminars, and practices. In addition, for over 19 years, Andersen has assembled a huge knowledge base and established a robust resource management institution.
• We have been strengthening our expertise since 2007. During this time, we have formed excellent teams with streamlined processes, where you can learn something new from your colleagues every day and enjoy your work.
• We are a cool young team of like-minded people communicating informally.
• You'll have a stable and competitive salary and an extensive benefits package.
• At Andersen, we have many different ways to grow. You can improve as a specialist or a manager, and all your activities will be decently rewarded.

Join us!

Локації

Worldwide