Machine Learning Engineer For Travel Management

????????BizAway provides travel management services and solutions for companies, focusing on sustainability, technology, and innovative processes.??????Design, develop, and deploy ML-powered data products that enhance the company’s value proposition and drive business impact Collaborate with Data Analysts to translate business needs and KPIs into modeling approaches Collaborate with Data Engineers to ensure robust data pipelines, feature availability, and production-ready systems Own the full lifecycle of ML models, from problem framing and experimentation to deployment, monitoring, and continuous improvement Ensure that models deliver measurable value over time Contribute to defining best practices for ML development, including model evaluation, versioning, and performance monitoring Promote a pragmatic and impact-driven approach to AI/ML within the company ??????????5-8 Years of experience in Machine Learning, Applied Data Science, or similar roles Strong proficiency in Python and common ML libraries, including scikit-learn, TensorFlow, and PyTorch Experience developing and deploying ML models in production environments Solid understanding of supervised and unsupervised learning Experience with feature engineering and real-world datasets Familiarity with APIs and model serving for batch and/or real-time inference Familiarity with Large Language Models and their use within end-to-end AI workflows Strong problem-solving skills and ability to translate business problems into ML solutions Ability to work independently and take ownership of projects end-to-end Master’s degree in Computer Science, Engineering, Mathematics, or a related field English proficiency, written and spoken, minimum B2 level Nice to have: PhD in a relevant discipline, experience with experimentation frameworks such as A/B testing and impact measurement, experience with cloud platforms such as AWS and containerization with Docker and Kubernetes, knowledge of MLOps practices including model deployment, versioning, monitoring, and retraining.???????Permanent contract Working hours: Full-time - 40h/week, from Monday to Friday Attractive compensation, including equity in the company Equity in the company through a stock options plan Opportunity to join a rapidly growing scale-up Opportunity to develop an entrepreneurial spirit and implement real-impact business decisions Multicultural and international team Collaborative environment for work and learning Free coffee and free beers.#J-*****-Ljbffr

5-8 Years of experience in Machine Learning, Applied Data Science, or similar roles Strong proficiency in Python and common ML libraries, including scikit-learn, TensorFlow, and PyTorch Experience developing and deploying ML models in production environments Solid understanding of supervised and unsupervised learning Experience with feature engineering and real-world datasets Familiarity with APIs and model serving for batch and/or real-time inference Familiarity with Large Language Models and their use within end-to-end AI workflows Strong problem-solving skills and ability to translate business problems into ML solutions Ability to work independently and take ownership of projects end-to-end Master’s degree in Computer Science, Engineering, Mathematics, or a related field English proficiency, written and spoken, minimum B2 level Nice to have: PhD in a relevant discipline, experience with experimentation frameworks such as A/B testing and impact measurement, experience with cloud platforms such as AWS and containerization with Docker and Kubernetes, knowledge of MLOps practices including model deployment, versioning, monitoring, and retraining.

Permanent contract Working hours: Full-time - 40h/week, from Monday to Friday Attractive compensation, including equity in the company Equity in the company through a stock options plan Opportunity to join a rapidly growing scale-up Opportunity to develop an entrepreneurial spirit and implement real-impact business decisions Multicultural and international team Collaborative environment for work and learning Free coffee and free beers. #J-*****-Ljbffr