Senior Software Engineer, Machine Learning

🕒 October 2

🇨🇦 Canada – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 10%

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Hive.co

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2014

📣 Marketing

💼 Consulting

📦 Logistics

Marketing • Consulting • Logistics

Hive. co is a comprehensive event marketing platform designed to help event promoters streamline their marketing strategies and enhance ticket sales. It integrates seamlessly with ticketing platforms to provide real-time event and ticket buyer data, allowing for targeted email and SMS campaigns. With features like CRM, automation, and detailed reporting, Hive. co enables event organizers to engage fans effectively, boost attendance, and optimize marketing efforts for festivals, music events, fairs, rodeos, and comedy shows. The platform simplifies data management and audience segmentation, making it a go-to solution for event promoters.

📋 Description

• Design and own a cloud-native big data platform handling audience data for millions of attendees and billions of interactions annually • Design and own ML infrastructure including feature stores, training pipelines, model serving, and monitoring • Ensure reliable, low-latency access to features and ML infrastructure • Own the full data pipeline from change data capture through validation, transformation, and denormalization • Connect data-system performance and reliability to customer and business outcomes • Build data products with defined SLAs, strong data health, and discoverability • Use AI coding agents such as Claude Code • Build LLM-powered pipelines and autonomous agents to enrich, classify, and act on audience data at scale • Collaborate with product and engineering teams and communicate technical decisions to stakeholders

🎯 Requirements

• 8+ years of hands-on data engineering experience • Proven track record designing, building, and operating large-scale distributed data and ML systems in production • Core ML foundations, including supervised/unsupervised learning, cross-validation, bias–variance, regularization, evaluation metrics, regression, tree ensembles, and clustering • Feature engineering with Python ML tooling, including pandas and scikit-learn; familiarity with PyTorch or TensorFlow • Experience with production ML pipelines and feature datasets for model training and inference • MLOps practices: experiment tracking, model versioning/registry, deployment, and monitoring for drift/data quality • Strong distributed systems foundations: partitioning strategies, consistency models, backpressure handling, fault tolerance, and capacity planning • Experience applying LLMs and agentic systems in production data or ML contexts • Product and commercial orientation with ability to frame technical decisions in terms of customer impact and business outcomes • Stakeholder communication skills for non-technical audiences • Programming experience with Python and Django • Experience with Clickhouse, MySQL, MongoDB, ElasticSearch, and Redshift • Experience with Airflow or Dagster • Comfortable operating independently in ambiguous, fast-changing environments • Skilled at troubleshooting complex ML systems • Nice to have: owning or re-architecting a data platform end-to-end • Nice to have: background in SaaS or event-driven products

🏖️ Benefits

• Meaningful salary and equity • 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

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