machine learning engineer

The company provides a comprehensive booking and procurement platform for travel industry professionals, supporting large transaction volumes and integrating with a global network of suppliers to streamline operations and enhance productivity.

• Design and maintain scalable ML pipelines;
• Build robust data ingestion, feature engineering, and model training pipelines to ensure reproducibility and production readiness;
• Deploy and monitor models in production;
• Lead model serving, track performance and data drift, and implement automated retraining triggers;
• Optimize model efficiency and infrastructure;
• Reduce inference latency and cost via quantization, pruning, GPU tuning, and distributed training;
• Establish MLOps best practices across teams;
• Implement CI/CD for models, versioning, and shared tooling to accelerate delivery;
• Collaborate with PMs and stakeholders to translate business needs into ML solutions and communicate risks;

• Experience developing and deploying production-grade ML solutions (NLP, computer vision, and/or time-series analytics) for 5+ years;
• Strong proficiency in Python and deep learning frameworks such as PyTorch and TensorFlow/Keras;
• Hands-on experience building and exposing ML models as services for integration by other applications;
• Experience with modern LLM and transformer-based approaches, including Hugging Face Transformers, RAG pipelines, and vector databases;
• Solid data engineering skills with tools such as Apache Spark/PySpark, Airflow, Kafka, and Databricks;
• Experience deploying and containerizing models using Docker and Kubernetes;
• Familiarity with ML lifecycle tooling and monitoring such as MLflow, Prometheus, and Grafana;
• Experience with OCR-based document processing and/or multimodal ML systems;
• Proficiency with data manipulation libraries: Pandas, Polars, NumPy, Dask;
• Experience working in Agile/Scrum teams with strong communication and collaboration skills;
• English level Upper-Intermediate or higher;
• Nice to have: Experience in travel domain, certificates.

• Competitive salary;
• Extensive benefits package;
• Access to educational platforms, seminars, and professional practices;
• Mentoring and adaptation systems;
• Transparent performance review and assessment systems.