Jobgether is looking for a Machine Learning Engineer to work at the intersection of data science and engineering. You will build and scale high-performance machine learning systems that power global fraud detection, focusing on productionising models, designing pipelines, and ensuring real-time predictions at scale.
What You'll Do
- Design, build, and manage scalable end-to-end ML pipelines, from raw data ingestion to model inference, optimized for terabyte-scale datasets.
- Collaborate with data scientists to deploy performant, scalable, and maintainable machine learning models into production.
- Implement workflow orchestration for multi-stage ML jobs using tools such as Prefect or similar frameworks.
- Enhance and oversee MLOps infrastructure, including model versioning, automated deployments, monitoring, and observability.
- Troubleshoot and resolve performance bottlenecks in production systems while ensuring system availability.
- Continuously improve internal tools, engineering practices, and automation to streamline ML workflows.
What We're Looking For
- Proven experience building and deploying machine learning models in production environments.
- Strong understanding of the ML lifecycle, with hands-on experience designing training pipelines for large datasets.
- Familiarity with workflow orchestration tools such as Prefect, Kubeflow, or Argo.
- Solid grounding in software engineering fundamentals, including data structures, design patterns, Git, CI/CD, testing, and monitoring.
- Excellent analytical and problem-solving skills, with the ability to work in ambiguous situations.
- Strong communication and teamwork skills, with the ability to collaborate across technical and non-technical audiences.
Nice to Have
- Knowledge of a systems programming language (Go, C++, Java, Rust).
- Knowledge of deep learning frameworks (PyTorch, TensorFlow).
- Knowledge of distributed data processing (Spark, Dataproc).
- Knowledge of data pipeline tools (dbt).
Technical Stack
- Prefect, Kubeflow, Argo
- PyTorch, TensorFlow
- Spark, Dataproc
- dbt
Benefits & Compensation
- Flexible working hours in a remote-first environment.
- Comprehensive BUPA health insurance.
- £1,000 annual wellness and learning budget.
- Monthly wellbeing and learning day (last Friday of each month).
- 25 days holiday plus bank holidays, plus 1 extra cultural day.
- Access to mental health support through Spill.
- Aviva pension scheme.
- Company-supported charitable initiatives and volunteering opportunities.
- Fortnightly randomised team lunches (in-person or remote).
- Cycle-to-work scheme.
- BorrowMyDoggy membership for dog lovers.
- Weekly board game nights and a dedicated social budget.
Work Mode
This is a remote position open to candidates based in the United Kingdom.
Jobgether is an equal opportunity employer.



