[Hiring] Senior Software Engineer, Machine Learning @hive.co

Role Description

As a Senior Data Engineer at Hive, you’ll play a vital role in evolving our data platform, which directly determines what our customers can do, how fast our product moves, and how confidently leadership can make bets. You'll own outcomes, not tickets. If a business metric is off and it touches data, that's yours to care about.

• Build our Data Platform:
  • Design and own a cloud-native big data platform handling audience data for millions of attendees and billions of interactions a year.
  • Build the infrastructure that determines the quality of every insight, recommendation, and decision Hive's customers make.
• Build our ML Platform:
  • Design and own the infrastructure that takes models from experiment to production — feature stores, training pipelines, model serving, and monitoring.
  • Ensure reliable, low-latency access to the features and infrastructure needed to build and ship models confidently.
  • Build observability to catch model degradation in production before it impacts customers.
• Own the Full Pipeline — and Its Business Impact:
  • Drive the stack end to end from Change Data Capture through validation, transformation, and denormalization.
  • Connect technical dots to business dots, understanding the impact of pipeline delays, metric drifts, or stale data on customers.
• Treat Data as a Product:
  • Ship data products that internal teams and customers depend on like a production API.
  • Define SLAs, obsess over data health, and build for discoverability.
• Build and Leverage Agentic Systems:
  • Bring an agentic engineering mindset to everything — both how you work and what you build.
  • Use AI coding agents as a force multiplier and build LLM-powered pipelines and autonomous agents that enrich, classify, and act on audience data at scale.

Qualifications

• 8+ years of hands-on data engineering experience, with a 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) and common algorithms (regression, tree ensembles, clustering).
• Feature engineering with Python ML tooling (pandas, scikit-learn; familiarity with PyTorch or TensorFlow).
• 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 — partitioning strategies, consistency models, backpressure handling, fault tolerance, and capacity planning.
• Experience applying LLMs and agentic systems in production data or ML contexts.
• A product and commercial orientation — framing technical decisions in terms of customer impact and business outcomes.

Requirements

• Comfortable operating independently and making progress in ambiguous, fast-changing environments.
• Biased toward action, willing to make decisions with imperfect information and iterate quickly.
• Skilled at troubleshooting complex ML systems and building durable solutions when things break.
• Excited to shape the future of Hive’s data/ML infrastructure and team in a high-growth, fast-paced company.

Nice to haves

• 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.

Compensation/Benefits Package

• Meaningful salary and equity: you're rewarded based on impact.
• Work fully remote from the comfort of your home.
• Flexible work hours: minimal meetings and no 9-5.
• Health & Dental coverage with Parental Leave top-ups in addition to EI benefits.
• Unlimited vacation/PTO: so you can be happy and healthy!

Company Description

Hive.co is a marketing platform for event marketers. We help brands personalize and automate their campaigns, using email and SMS, to empower them to sell out so they can focus on making their events unforgettable.

By integrating with ticketing partners like Ticketmaster and e-commerce partners like Shopify, we enable brands to access and act on all their customer data, so they can easily segment their list in thousands of ways, and send more customized, timely email campaigns that land in inboxes.

We started our company inside a University of Waterloo computer lab in early 2014, graduated from Y Combinator that summer (S14 batch) and have been growing ever since. Originally based in Kitchener, our team is now 100% remote and located all across Canada!