Senior Machine Learning Engineer
Tasks
- Automate testing and validation
- Build and deploy ML and GenAI solutions
- Build reusable engineering assets
- Build web APIs for AI serving
- Collaborate with data scientists and engineers
- Conduct code reviews and design reviews
- Design production AI services
- Develop Infrastructure-as-Code patterns
- Document controls and auditability expectations
- Implement MLOps and LLMOps pipelines
- Implement observability for AI services
- Integrate data pipelines into AI services
- Manage model versioning and lifecycle
- Monitor model performance and drift
- Operate and support AI services
- Package and release models
- Productionise proof of concept into production
- Set up CI CD for ML
- Translate business requirements into technical designs
Perks/Benefits
- Contributory pension scheme
- Enhanced Adoption Pay
- Enhanced maternity pay
- Private healthcare
- Professional development opportunities
Skills/Tech-stack
API | CI/CD | Docker | FastAPI | Flask | Generative AI | Git | Infrastructure as Code | Kubernetes | LLM orchestration | LLMOps | Logging | MLOps | Machine Learning | Metrics | Model Drift | Model Monitoring | Observability | PostgreSQL | PyTorch | Python | RAG | Retrieval-Augmented Generation | SQL | TensorFlow | Tool-Calling | Tracing | “as-code”
Education
N/A
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