Machine Learning Engineer
Tasks
- Collaborate with Data Scientists on model development
- Collaborate with infrastructure teams to deploy models cleanly
- Conduct model evaluation and inference cost improvements
- Define ML engineering standards for reproducibility and model review
- Deploy machine learning models to production
- Implement retraining triggers and retraining logic
- Improve model reliability through testing and code review
- Monitor model drift and data quality
- Perform feature engineering and feature label validation
- Serve machine learning models and monitor performance
- Validate training data integrity and prevent data leakage
Perks/Benefits
- Early Friday finish
- Extra wellbeing days off
- Flexible working
- Free Headspace subscription
- Hybrid working
- Remote work
- Summer and winter conferences
- Travel once per month to London office
- Uni fund for learning
- Wellbeing fund
- Year round celebrations
Skills/Tech-stack
AWS | Azure | CI/CD | Code review | Data Drift | Data Quality | Data Skew | Data leakage | Databricks | Evaluation | Feature Engineering | Feature Store | Forecasting | LLM | MLflow | Machine Learning | Model Deployment | Model Monitoring | Model Registry | Model retraining | Optimization | Orchestration | Python | RAG | Recommendation Systems | Snowflake | Testing | Version control
Education
N/A
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