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About the Role
We are looking for a Senior Machine Learning Engineer to join a cross-functional team focused on growing our product algorithmic recommendations. This role involves evolving, improving, and innovating machine learning and AI capabilities across the platform. As a Senior Engineer, you will drive architecture, write scalable code, mentor engineers, and challenge teams to achieve excellence. You will collaborate with internal and external teams, embracing inner-sourced development and taking ownership from discovery to production.
Responsibilities
- Collaborate with Data Scientists, Product Managers, and Backend Engineers to bridge the gap between model development and production systems.
- Lead the architectural design of end-to-end ML systems, including data ingestion, training pipelines, inference, and monitoring.
- Transform data science prototypes into robust, scalable, and secure production software, owning the 'path to production'.
- Drive the adoption of MLOps best practices (CI/CD for ML, model versioning, feature stores) to accelerate feedback loops.
- Communicate ML system complexities (e.g., latency vs. accuracy trade-offs) to technical and non-technical stakeholders.
- Build and maintain a strong network across Data and Engineering organizations to ensure seamless ML system integration.
- Lead projects, mentor peers, and advocate for engineering excellence within the data science domain.
Requirements
- Proficiency in Python and a strong understanding of software engineering principles (OO design, patterns, testing) applied to Machine Learning.
- Demonstrable experience designing and operating ML systems in production, including familiarity with serving patterns (e.g., REST APIs, batch inference, event-driven).
- Experience with orchestration tools (e.g., Airflow, Dagster).
- Experience with cloud-native ML platforms (e.g., AWS SageMaker, GCP Vertex AI).
- Ability to influence decision-making regarding infrastructure and tooling, balancing 'build vs. buy' discussions.
- Strong knowledge of Infrastructure as Code (Terraform).
- Strong knowledge of containerization (Docker/Kubernetes).
- Familiarity with data engineering fundamentals (SQL, distributed data processing) to debug and optimize data flows.
- A proactive mindset to automate manual processes.
- A passion for improving the developer experience for Data Scientists.
Skills
- Python
- Machine Learning
- Software Engineering Principles
- OO Design
- Design Patterns
- Testing
- ML System Design
- ML System Operation
- REST APIs
- Batch Inference
- Event-Driven Architecture
- Airflow
- Dagster
- AWS SageMaker
- GCP Vertex AI
- Infrastructure as Code
- Terraform
- Docker
- Kubernetes
- SQL
- Distributed Data Processing
Location
- Bristol
- London
Work Type
- Hybrid
- Full-time
Experience Level
- Senior
About the Company
- We're a leading global online food delivery platform, and our vision is to empower everyday convenience.
- Our teams forge connections internally and work with some of the best-known brands on the planet, giving us truly international impact in a dynamic environment.
- Fun, fast-paced and supportive, the JET culture is about movement, growth and about celebrating every aspect of our JETers.
- Thanks to them we stay one step ahead of the competition.
Equal Opportunity
- No matter who you are, what you look like, who you love, or where you are from, you can find your place at Just Eat Takeaway.com.
- We're committed to creating an inclusive culture, encouraging diversity of people and thinking, in which all employees feel they truly belong and can bring their most colourful selves to work every day.