Senior 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 240+ employees from different nationalities and backgrounds working across France 🇫🇷, 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 currently looking for a Senior Machine Learning Engineer, based in Warsaw, Poland, to contribute to the ML engineering efforts within a highly talented team of Data Scientists and ML Engineers. You'll work on 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 senior engineer, you will focus on impact-driven, iterative delivery, balancing speed and quality while actively managing dependencies and coordinating with stakeholders to ensure timely and high-quality feature delivery. You will own end-to-end implementation of medium-to-high complexity projects and help maintain clear communication between engineering and product teams.

Our hybrid working model is 3 days/week in the office.

What will you be doing? 🤔

Build and Scale ML Services: 

Design, implement, and optimize ML platform components, enabling efficient development and deployment of ML-driven features & products.

End-to-End Ownership: 

Work on 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: Support training, storage, retrieval, deployment, and automated retraining of models.

- Monitoring Dashboards: Implement and maintain real-time performance and system health monitoring dashboards.

- CI/CD Pipelines: Contribute to testing, validation, and deployment of ML assets (code, pipelines, models) with CI/CD workflows.

Ensure Engineering Excellence:

You will contribute to architectural decisions, participate in PR and RFC reviews, and ensure code quality. You will help prioritise and resolve tech debt while mitigating scalability and performance risks.

Enhance Operational Excellence: 

You will ensure monitoring and alerting are in place, participate in postmortems, and implement MLOps best practices for stability and efficiency.

What do we need from you? 😎

- 3+ 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: Expertise in building ML infrastructure for event-driven and batch pipelines via Kafka, PySpark, Airflow, DBT, Docker, and Kubernetes. Nice-to-have are skills in optimizing AWS services like S3, Redshift, and EKS for scalability and cost efficiency.

- Strong communication skills and ability to articulate complex technical concepts to diverse audiences in English, aligning technical solutions with strategic business goals.

- Adaptability to excel in fast-changing, ambiguous environments while delivering robust technical solutions.

If you’re passionate about technology, team player, eager to learn, and ready to grow, we encourage you to apply even if you don’t meet all the requirements.

• Work in an international, dynamic and passionate environment with a company culture focused on learning and development 🎉
• Hybrid working model and flexible hours ✨

• Meal Vouchers (40zł daily‎) 🥗
• Stuart Academy, offering a wide range of upskilling and development opportunities 🎓
• Wellness Allowance with our partner Juno 171 zł / month 🧘
• Private healthcare provided by Luxmed 🧑‍⚕️
• Work-from-Abroad policy (enjoy 30 days per year working from anywhere!) 🏞

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 company’s 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 🙌

Stuart is proud to be an equal opportunity workplace dedicated to promoting diversity. We don’t discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status or disability status 💙

Please note: Our Talent Acquisition Team is international coming from across the world 🌍 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 🤗

Want to learn more about us? Visit https://stuart.com/about-us/