TA
Machine Learning Engineer
- Hiring from
- Germany
- Work type
- Hybrid
- Posted
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About The Company
Lieferando is a leading online food delivery platform operating in multiple countries, dedicated to connecting customers with their favorite local restaurants and grocery providers. As part of the Just Eat Takeaway.com group, Lieferando strives to enhance everyday convenience through innovative technology solutions. Our mission is to provide seamless, reliable, and efficient delivery services, ensuring that customers can enjoy their meals or essentials with just a few clicks. We foster a dynamic and inclusive work environment that encourages innovation, collaboration, and continuous learning, enabling our team members to thrive and contribute to our global success.
About The Role
We are seeking a highly skilled Machine Learning Engineer to join our Estimations department at Lieferando. In this role, you will be instrumental in developing and deploying advanced machine learning models that optimize our logistics and delivery operations. Reporting directly to the Data Science Manager, you will work within a talented team of developers, engineers, analysts, and researchers to create intelligent applications that enhance decision-making processes across our platform. This position offers a hybrid work arrangement, requiring three days onsite in our Berlin office and two days remote, providing flexibility while fostering collaboration.
The successful candidate will have a passion for leveraging machine learning to solve complex logistics challenges, including predicting delivery ETAs, optimizing routing, and improving pricing strategies. Your work will directly impact the efficiency, reliability, and profitability of our services, ensuring that Lieferando remains at the forefront of the food delivery industry. You will collaborate closely with cross-functional teams to translate innovative ideas into scalable, production-ready solutions that meet real-world demands.
Qualifications
At Lieferando, we value our team members and offer a comprehensive benefits package designed to support your professional growth and personal well-being. Our benefits include competitive salary packages, health insurance, and flexible working arrangements. We promote a healthy work-life balance through generous paid time off, remote work options, and wellness programs. Additionally, employees have access to ongoing learning and development opportunities, including training, workshops, and conferences. We foster an inclusive culture that celebrates diversity and encourages innovation, ensuring every team member feels valued and empowered to contribute their best.
Equal Opportunity
Lieferando is an equal opportunity employer committed to fostering an inclusive environment for all employees. We do not discriminate based on race, ethnicity, gender, age, sexual orientation, disability, religion, or any other protected characteristic. We believe that diverse perspectives and experiences drive innovation and excellence, and we are dedicated to creating a workplace where everyone feels a sense of belonging and can thrive. We encourage applications from all qualified individuals and are committed to providing equal employment opportunities across our organization.
Lieferando is a leading online food delivery platform operating in multiple countries, dedicated to connecting customers with their favorite local restaurants and grocery providers. As part of the Just Eat Takeaway.com group, Lieferando strives to enhance everyday convenience through innovative technology solutions. Our mission is to provide seamless, reliable, and efficient delivery services, ensuring that customers can enjoy their meals or essentials with just a few clicks. We foster a dynamic and inclusive work environment that encourages innovation, collaboration, and continuous learning, enabling our team members to thrive and contribute to our global success.
About The Role
We are seeking a highly skilled Machine Learning Engineer to join our Estimations department at Lieferando. In this role, you will be instrumental in developing and deploying advanced machine learning models that optimize our logistics and delivery operations. Reporting directly to the Data Science Manager, you will work within a talented team of developers, engineers, analysts, and researchers to create intelligent applications that enhance decision-making processes across our platform. This position offers a hybrid work arrangement, requiring three days onsite in our Berlin office and two days remote, providing flexibility while fostering collaboration.
The successful candidate will have a passion for leveraging machine learning to solve complex logistics challenges, including predicting delivery ETAs, optimizing routing, and improving pricing strategies. Your work will directly impact the efficiency, reliability, and profitability of our services, ensuring that Lieferando remains at the forefront of the food delivery industry. You will collaborate closely with cross-functional teams to translate innovative ideas into scalable, production-ready solutions that meet real-world demands.
Qualifications
- Proven experience in machine learning, particularly in developing real-time data streaming technologies for logistics or delivery products.
- Strong proficiency in Python programming and software engineering best practices.
- Hands-on experience deploying machine learning models in cloud environments such as Amazon Web Services (AWS) or Google Cloud Platform (GCP).
- Familiarity with microservices architecture, event-driven systems, serverless computing, and cloud-native patterns.
- Experience working with containerization and orchestration tools like Kubernetes, Docker, and deployment pipelines.
- Knowledge of workflow orchestration tools such as Airflow or MLflow is a plus.
- Ability to work independently, solve complex problems, and communicate effectively within multi-disciplinary teams.
- Experience managing high-scale production systems with millions of requests per day is advantageous.
- Research, implement, and deploy innovative machine learning techniques tailored to logistics and supply chain challenges.
- Scale and adapt novel ML solutions to enhance decision-making across various product use cases.
- Develop, test, and optimize data pipelines, tools, and evaluation frameworks that support continuous improvement of ML models.
- Collaborate with cross-functional teams to integrate ML applications with front-facing solutions, ensuring seamless user experiences.
- Monitor and maintain production ML systems, ensuring performance, reliability, and scalability.
- Document methodologies, models, and processes to facilitate knowledge sharing and future development.
- Stay updated with the latest advancements in machine learning and logistics technologies, applying best practices to our solutions.
At Lieferando, we value our team members and offer a comprehensive benefits package designed to support your professional growth and personal well-being. Our benefits include competitive salary packages, health insurance, and flexible working arrangements. We promote a healthy work-life balance through generous paid time off, remote work options, and wellness programs. Additionally, employees have access to ongoing learning and development opportunities, including training, workshops, and conferences. We foster an inclusive culture that celebrates diversity and encourages innovation, ensuring every team member feels valued and empowered to contribute their best.
Equal Opportunity
Lieferando is an equal opportunity employer committed to fostering an inclusive environment for all employees. We do not discriminate based on race, ethnicity, gender, age, sexual orientation, disability, religion, or any other protected characteristic. We believe that diverse perspectives and experiences drive innovation and excellence, and we are dedicated to creating a workplace where everyone feels a sense of belonging and can thrive. We encourage applications from all qualified individuals and are committed to providing equal employment opportunities across our organization.