5 days ago
London, United KingdomSenior
Responsibilities
- Collaborate with Data Scientists, Product Managers, and Backend Engineers to connect model development with production systems.
- Lead the architecture of end-to-end ML systems, including data ingestion, training pipelines, real-time inference, and monitoring infrastructure.
- Convert data-science prototypes into robust, scalable, secure production software and own the path to production.
- Drive MLOps practices including model versioning and feature stores to improve the data-science feedback loop.
- Communicate ML system trade-offs such as latency versus accuracy to technical and non-technical stakeholders.
- Build relationships across Data and Engineering organizations to integrate ML systems with the wider platform.
- Lead projects, mentor engineers, and promote engineering excellence within the data-science domain.
Requirements
- Proficiency in Python and strong software engineering principles applied to machine learning, including object-oriented design, patterns, and testing.
- Demonstrable experience designing and operating production ML systems beyond notebook-based model training.
- Familiarity with ML serving patterns including batch inference and event-driven systems.
- Experience with orchestration tools such as Airflow or Dagster and cloud-native ML platforms such as AWS SageMaker or GCP Vertex AI.
- Ability to influence infrastructure and tooling decisions and evaluate build-versus-buy trade-offs.
- Strong knowledge of Infrastructure as Code using Terraform and containerization with Docker and Kubernetes.
- Familiarity with SQL and distributed data-processing fundamentals for debugging and optimizing data flows.
- Proactive approach to automating manual processes and improving the developer experience for Data Scientists.
Benefits
- Hybrid full-time role based in Bristol or London, with 3 days per week in the office and 2 days working from home.
- Opportunity to build and own production ML systems affecting millions of customers daily.
- Inclusive, supportive, and international working environment with opportunities for collaboration and growth.
Tech Stack
Categories
About Just Eat
Just Eat Takeaway.com builds an online food-delivery and convenience marketplace that connects consumers with restaurants, grocery, and retail partners, supported by courier logistics and merchant tools. It earns primarily through commissions and delivery fees on orders placed via its apps and website. Headquartered in Amsterdam, the company was formed by the 2020 merger of Just Eat and Takeaway.com and is publicly listed on the London and Amsterdam stock exchanges.