LEAD MACHINE LEARNING ENGINEER

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 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 today’s 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 , Italy , Poland , Spain and the UK.
It’s 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 The role 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? 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? - 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.