Stuart is a leading tech-enabled logistics platform that transforms on-demand delivery across sectors like food, grocery, and retail. Operating in over 130 cities across Europe, Stuart connects businesses with a network of independent couriers, providing access to fast, flexible, and efficient deliveries.
Our Mission đ
We are an impact-driven company that aims to build the future of logistics for a more sustainable world: shared, efficient and reliable. We are committed to creating a new standard for urban deliveries that meet todayâs environmental and social challenges while offering a premium delivery experience blending speed, flexibility and convenience.
Stuart is a highly diverse and inclusive company of 280+ employees from different nationalities and backgrounds working across France đŤđˇ, Italy đŽđš, Poland đľđą, Spain đŞđ¸ and the UK. đŹđ§
Itâs the right moment and the right place for us to make an impact on millions of people, as home delivery services hit a record high. And guess what? You can help us fulfil our vision đ
The role â¨
We are looking for a Lead Machine Learning Engineer, based in Barcelona, Spain, to drive the Machine Learning (ML) engineering efforts within a highly talented team of Data Scientists and ML Engineers. You'll take charge of critical initiatives that enable the team to develop, deploy, and scale innovative machine learning services in domains such as real-time courier incentive & positioning optimization, prediction of estimated times of arrival (ETAs) & risk signals throughout the package lifecycle, and fraud detection.
As a technical leader, you'll not only make key decisions to improve data quality and model performance but also play a hands-on role in building and optimizing advanced solutions to deliver impactful ML products at scale.
Our hybrid working model is 3 days/week in the office.
What will you be doing? đ¤
Build and Scale ML Services:
Lead the design, implementation, and optimization of our ML backend, enabling the efficient development and deployment of new ML driven features & products.
End-to-End Ownership:
Own ML services from prototype to production, ensuring performance, reliability, and scalability. This includes:
- PySpark Pipelines: Design and implement efficient pipelines for large-scale training data preprocessing.
- Real-Time Inference with Kafka: Integrate real-time data streaming and model inference.
- APIs for Real-Time Predictions: Develop and deploy RESTful APIs to serve models for real-time inference.
- ML Model Lifecycle Management: Oversee training, storage, retrieval, deployment, and automated retraining of models applying MLOps best practices.
- Monitoring Dashboards: Implement and maintain real-time performance and system health monitoring dashboards.
- CI/CD Pipelines: Automate testing, validation, and deployment of ML assets (code, pipelines, models) with CI/CD workflows.
Mentor and Lead:
Guide and mentor team members, fostering a high-performing, learning-driven engineering culture.
Help Shape our Product Strategy:
Collaborate on product strategy, contribute to roadmap planning, and drive technical decisions across our ML stack.
What do we need from you? đ
- Background: 5+ years of hands-on ML engineering experience in production environments, developing data and feature engineering pipelines, optimizing and deploying ML models, and integrating solutions into production systems.
- Software Engineering Expertise: Advanced level in Python with deep knowledge of data structures, algorithms, object-oriented programming, and CI/CD workflows. A nice-to-have would be another language, ideally Scala.
- ML Infrastructure and Cloud Proficiency: Strong expertise in building ML infrastructure for event-driven and batch pipelines via Kafka, PySpark, Airflow, DBT, Docker, and Kubernetes. Skilled in optimizing AWS services like S3, Redshift, and EKS for scalability and cost efficiency.
- Collaborative Communication: Excellent skills in articulating complex technical concepts to diverse audiences, aligning technical solutions with strategic business goals.
- Adaptability: Proven ability to excel in fast-changing, ambiguous environments while delivering robust technical solutions.
At Stuart, we believe that employees today want to evolve in collaborative, high-growth environments where they can demonstrate their abilities and thrive both professionally and personally. We are convinced that employees need to find alignment between their inner values and their companyâs culture and mission to unlock their full potential. We work to create a culture of empowerment, continuous learning and growth where everyone can bring expertise, own projects and easily measure their impact đ
Stuart is proud to be an equal opportunity workplace dedicated to promoting diversity. We donât discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status or disability status đ
Please note: Our Talent Acquisition Team is international coming from across the world đ We kindly ask you to please submit your CV and application in English so that it can be reviewed correctly (unless the job posting is in a language other than English). Thank you đ¤
Want to learn more about us? Visit https://stuart.com/about-us/
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Stuart, a dynamic tech-enabled logistics platform transforming on-demand delivery in sectors like food, grocery, and retail, is on the lookout for a Lead Machine Learning Engineer in Barcelona. This is a fantastic opportunity to join an impact-driven company dedicated to creating a sustainable future for urban logistics. As the Lead Machine Learning Engineer, you will work closely with a talented team of Data Scientists and ML Engineers to push the boundaries of what's possible in the field of machine learning. You'll be tasked with driving initiatives focused on real-time courier optimization, ETA predictions, and even fraud detection. Your role includes designing and implementing our ML backend, maintaining robust pipelines, and building APIs for real-time predictions. With 5+ years of hands-on experience in ML engineering, youâll have the chance to lead projects from prototype to production, ensuring scalability and performance. Additionally, Stuart's hybrid working model allows for three days in the office and two days remote, perfect for a balanced work-life blend. Join us as we shape the future of logistics and deliver impactful machine learning solutions that make a difference in the world. Your contributions will be valued, and you'll find our culture fosters continual learning and growth!
Stuart's ambition is to transform the on-demand delivery market.
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