Canada Life UK is building CreateOS — a next-generation operating system for modern record labels — and AI is at the center of it. As a Machine Learning Engineer, you will be a core builder on the team responsible for designing, training, deploying, and maintaining the ML systems that power intelligent automation, forecasting, anomaly detection, and agentic workflows across the platform. This is a hands-on engineering role for someone who is equally comfortable prototyping a new model and shipping it to production.
What You'll Do
- Build and maintain ML models for forecasting, anomaly detection, classification, ranking, and optimization across music industry use cases
- Partner with Analytics & BI to identify, engineer, and validate features that drive meaningful predictive power
- Own the full ML lifecycle — from problem framing and data exploration through training, evaluation, deployment, and monitoring
- Deploy and monitor models in production using modern MLOps tooling
- Instrument models for performance tracking, drift detection, and continuous improvement
- Implement CI/CD, automated testing, model versioning, and observability for all ML systems
- Collaborate with Data Engineering to ensure data quality, feature delivery, and pipeline reliability
- Develop and maintain modular AI agents that automate multi-step workflows across CreateOS
- Build and iterate on RAG pipelines, retrieval architectures, and semantic search systems grounded in structured business data
- Implement guardrails, evaluation frameworks, and safe action boundaries for agentic systems
- Translate business problems from non-technical stakeholders into well-scoped ML solutions
- Document model design decisions, evaluation results, and known limitations clearly
- Contribute to a culture of engineering rigor and responsible AI development
What We're Looking For
- 4+ years of software engineering experience in a production environment, with exposure to ML or data science work; OR 2+ years of experience specifically as an ML Engineer or Applied Data Scientist
- Strong proficiency in Python and ML frameworks such as PyTorch, scikit-learn, or XGBoost
- Hands-on experience building, deploying, and monitoring models in cloud environments — GCP strongly preferred
- Solid understanding of modern ML techniques and their mathematical foundations
- Experience with LLMs and prompt engineering, including building RAG systems or LLM-powered features
- Comfortable working with structured and unstructured data at scale
- Strong communication skills with the ability to explain complex model behavior to non-technical audiences
Nice to Have
- MS in Machine Learning, Data Science, Computer Science, or a related quantitative field; OR 4+ years of experience as an ML Engineer or Applied Data Scientist in lieu of an advanced degree
- Experience at a startup or high-growth technology company where you owned features end-to-end
- Familiarity with agentic frameworks such as LangChain, LangGraph, or AutoGen
- Background in music, media, entertainment, or rights/royalties data
- Experience with ontology design, knowledge graphs, or semantic data modeling
- Contributions to open-source ML projects or published research
- Familiarity with AI evaluation practices
Technical Stack
- Languages & Frameworks: Python, PyTorch, scikit-learn, XGBoost
- Cloud Platforms: GCP, AWS, Azure
- GCP Services: Vertex AI, BigQuery, Cloud Functions, Cloud Run
- AI Systems: LLMs, RAG
Team & Environment
You will work directly with the VP of AI & ML Engineering and partner closely with Data Engineering, Analytics, and Product.
