Senior Software Engineer, Machine Learning

Hive
Toronto
Workplace: RemoteFull timeFunction: Solutions Engineering & Sales EngineeringExperience: 8+ yearsSkills: ["Troubleshooting","Stakeholder communication","Independent execution","Decision making"]

Own Hive’s cloud-native data and ML platforms that power event marketing for millions of attendees. Build the infrastructure behind production audience data, end-to-end pipelines (including CDC, validation, and denormalization), and model infrastructure from experiment to production with monitoring and drift/data quality observability. Treat data as a product with SLAs and data health, and apply an agentic/LLM mindset to enrich, classify, and automate audience workflows.

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FursaFursa
Hive
Hive
1 month ago

Senior Software Engineer, Machine Learning

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Source: Company careers pageValidated by: Fursa AI
Last checked: 1 hour agoStatus: Live

Job Summary

Own Hive’s cloud-native data and ML platforms that power event marketing for millions of attendees. Build the infrastructure behind production audience data, end-to-end pipelines (including CDC, validation, and denormalization), and model infrastructure from experiment to production with monitoring and drift/data quality observability. Treat data as a product with SLAs and data health, and apply an agentic/LLM mindset to enrich, classify, and automate audience workflows.
Location: Toronto
Workplace: Remote
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Design and own a cloud-native big data platform for large-scale audience data powering customer insights, recommendations, and decisions.
  • •Build ML platform infrastructure to move models from experiment to production, including feature stores, training pipelines, model serving, and monitoring.
  • •Own end-to-end data pipelines from change data capture through validation, transformation, and denormalization while connecting failures to business impact.
  • •Treat data as a product by defining SLAs, ensuring data health, and improving discoverability for internal teams and customers.
  • •Build and leverage agentic systems and LLM-powered pipelines/agents to enrich, classify, and act on audience data at scale.

Pay and Benefits

Equity and Bonus:Equity
Perks:Remote WorkHealth InsuranceDentalParental LeavePaid Leave

Key Requirements

  • •8+ years of hands-on data engineering experience building and operating large-scale distributed data and ML systems in production with real SLAs.
  • •Strong core ML foundations (e.g., supervised/unsupervised learning, cross-validation, bias–variance, regularization, eval metrics) and algorithms like regression, tree ensembles, and clustering.
  • •Feature engineering experience using Python ML tooling such as pandas and scikit-learn (and familiarity with PyTorch or TensorFlow).
  • •Experience building production ML pipelines and MLOps practices including experiment tracking, model versioning/registry, deployment, and monitoring for drift/data quality.
  • •Distributed systems fundamentals (partitioning, consistency models, backpressure, fault tolerance, capacity planning) and experience applying LLMs/agentic systems in production data or ML contexts.
Experience:8+ years
Skills:TroubleshootingStakeholder communicationIndependent executionDecision making
Tech Stack:PythonDjangoClickhouseMySQLMongoDBElasticSearchRedshiftAirflowDagsterPyTorchTensorFlowPandasScikit-learnLLMsClaude Code

Company Brief

Hive
Provides a marketing automation platform (email, SMS, CRM, ads) tailored to event promoters and ticketing partners to drive ticket sales and audience engagement through data-driven campaigns and automation.
Industry: Events & Live Entertainment
Company Size: Medium (51 to 250 employees)
Revenue: USD 1M to 5M
Headquarters: Kitchener, Canada
Founded: 2014
Glassdoor
Glassdoor: 3.5
WebsiteLinkedInGlassdoor