Senior Machine Learning Engineer – Babbel Labs

• Own real personalisation and mastery-tracking subsystems end to end

• Work with the Principal Scientist to take designs from specification into production

• Shape new features from the beginning, beyond implementing predefined specifications

• Improve the personalisation engine independently and make confident technical decisions

• Design rigorous offline benchmarks against real baselines and online experiments to validate changes

• Instrument systems, monitor for silent failures, and resolve issues before incidents occur

• Operate and maintain production ML systems over time

• Deliver software using coding agents and verify their output

• Strong, hands-on ML engineering experience shipping real models to production
• Experience with recommendation, ranking, scoring, or trust-and-safety systems under real user load
• Experience with probabilistic modeling, latent-variable modeling and Bayesian inference, or equivalent rigor from an adjacent domain
• Experience evaluating ML systems, defining monitoring metrics, debugging anomalous outputs, and safely rolling out changes to live scoring or ranking systems
• Rigorous experimentation practice, including benchmarking against a real baseline and running or correctly interpreting A/B tests
• Type Script and Python as primary languages
• Sufficient AWS, Terraform, and CI/CD knowledge to ship and own service delivery
• Experience using coding agents daily and verifying their output
• Nice to have: psychometric models such as Item Response Theory
• Nice to have: graph ML experience, including embeddings, graph neural networks, or relational modeling at scale
• Nice to have: public technical work such as open-source contributions, writing, or competitive ML

Demonstrates expertise in Machine Learning Engineering, with a focus on shipping models to production, evaluating ML systems, and conducting rigorous experimentation. Proficient in Type Script and Python, with experience in AWS, Terraform, and CI/CD for effective service delivery.

• Machine Learning Engineering
• Production Model Deployment
• Probabilistic Modeling
• A/B Testing
• AWS and Terraform

• Machine Learning
• Probabilistic Modeling
• Latent-Variable Modeling
• Bayesian Inference
• Type Script
• Python
• Benchmarking
• Debugging
• Graph ML
• Item Response Theory

• Technical Decision-Making
• Independent Problem-Solving

• Personalisation Engine
• Recommendation Systems
• Ranking Systems
• Scoring Systems
• Trust-and-Safety Systems

• AWS
• Terraform
• CI/CD
• Coding Agents