Senior Machine Learning Engineer
New
R
RavelinFraud Detection
United KingdomFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- GitKubeflowMachine LearningPyTorchTensorflowMLOps
Requirements
- Experience designing, building, and deploying complex machine learning systems in a production environment.
- Deep understanding of the full machine learning lifecycle from research to deployment.
- Track record of leading the design and implementation of scalable training pipelines for large datasets.
- Experience with deep learning frameworks like PyTorch or TensorFlow.
- Experience with distributed/multi-GPU training and transformer architectures.
- Familiarity with modern workflow orchestration tools such as Prefect, Kubeflow, or Argo.
- Experience leading complex, cross-functional projects and influencing technical direction.
- Strong software engineering fundamentals, including data structures, design patterns, and version control (Git).
- Experience with CI/CD, testing, and monitoring best practices.
- Strong problem-solving skills and the ability to navigate ambiguity.
- Collaborative mindset and strong communication skills.
Responsibilities
- Lead the design, architecture, and orchestration of scalable and reliable end-to-end ML pipelines.
- Develop high-throughput data pipelines optimized for multi-GPU training of foundational transaction models.
- Propose and champion new machine learning methods and tools to influence the technical roadmap.
- Drive cross-functional initiatives with Data Engineering and Infra teams to align on data architecture.
- Evolve MLOps infrastructure, including strategy for model versioning, automated deployments, monitoring, and observability.
- Mentor and guide team members through code reviews, design discussions, and knowledge sharing.
- Champion and contribute to the continuous improvement of internal tools and engineering best practices.
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