Hive.Co
Senior Software Engineer, Machine Learning
Canada (Remote). Posted a month ago
The role
You will design and own a cloud-native big data platform and an ML platform. You will build infrastructure for feature stores, training pipelines, model serving, and monitoring.
What you will do
- Design and own a cloud-native big data platform
- Design and own ML infrastructure including feature stores, training pipelines, model serving, and monitoring
- Drive the full pipeline from Change Data Capture through validation, transformation, and denormalization
- Treat data as a product by defining SLAs and building for discoverability
- Build and leverage agentic systems and LLM-powered pipelines
Required qualifications
- 8+ years of hands-on data engineering experience
- Proven track record of designing, building, and operating large-scale distributed data and ML systems in production
- Core ML foundations (supervised/unsupervised, cross-validation, bias–variance, regularization, eval metrics)
- Common algorithms (regression, tree ensembles, clustering)
- Feature engineering with Python ML tooling (pandas, scikit-learn)
- Production ML pipelines and feature datasets feeding model training and inference
- MLOps practices: experiment tracking, model versioning/registry, deployment, and monitoring for drift/data quality
- Strong foundations in distributed systems principles
- Experience applying LLMs and agentic systems in production data or ML contexts
- Product and commercial orientation
- Stakeholder communication skills
Nice to have
- History of owning or re-architecting a data platform end-to-end in a fast-growing environment
- Background in SaaS or event-driven products where data systems directly power user-facing features
Benefits
- Meaningful salary and equity
- Work fully remote
- Flexible work hours
- Health & Dental coverage
- Parental Leave top-ups in addition to EI benefits
- Unlimited vacation/PTO
About the company
Hive.co is a marketing platform for event marketers that helps brands personalize and automate campaigns. The team is 100% remote and located across Canada.