Senior Software Engineer, Data Systems

This is a fully remote position, open to applicants in Canada.

📋 Description

• Design and take ownership of a cloud-native big data platform that manages audience data for millions of participants and billions of interactions each year.

• Develop and manage machine learning infrastructure, which includes feature stores, training pipelines, model serving, and monitoring.

• Construct reliable, low-latency feature and model infrastructure.

• Oversee the entire data pipeline from change data capture to validation, transformation, and denormalization.

• Link data system performance to customer impact and business outcomes.

• Treat data as a product by establishing service level agreements (SLAs), enhancing data quality, and promoting discoverability.

• Utilize AI coding agents, such as Claude Code.

• Create pipelines powered by large language models (LLMs) and autonomous agents to enrich, classify, and act on audience data at scale.

• Diagnose complex machine learning systems and develop sustainable solutions.

• Collaborate with product and engineering teams in an uncertain, rapidly evolving environment.

• Contribute to the development of Hive’s data and machine learning infrastructure and team.

⛳️ Requirements

• Over 8 years of practical experience in data engineering.

• Demonstrated experience in designing, building, and managing large-scale distributed data and machine learning systems in a production setting.

• Proficient in handling high-throughput event streams, production SLAs, and understanding the consequences of failures.

• Knowledgeable in supervised and unsupervised learning, cross-validation, bias–variance trade-off, regularization, and evaluation metrics.

• Familiar with regression, tree ensembles, and clustering algorithms.

• Experienced with Python machine learning tools, including pandas and scikit-learn.

• Comfortable with PyTorch or TensorFlow.

• Proven experience in constructing production machine learning pipelines and feature datasets for model training and inference.

• MLOps experience encompassing experiment tracking, model versioning and registry, deployment, and monitoring of drift and data quality.

• Strong foundational knowledge in distributed systems, including partitioning, consistency models, backpressure, fault tolerance, and capacity planning.

• Production experience applying large language models and agentic systems within data or machine learning contexts.

• Product and commercial mindset with the ability to relate technical choices to customer impact and business outcomes.

• Effective communication skills for engaging with non-technical stakeholders.

• Capability to work independently in unclear and rapidly changing environments.

• Strong troubleshooting abilities for complex machine learning systems.

• Nice to have: experience in end-to-end data platform ownership or re-architecture.

• Nice to have: experience with SaaS or event-driven products.

• Must be eligible to work in Canada without current or future employer sponsorship.

🏝️ Benefits

• Competitive salary and equity options.

• Fully remote work, allowing you to operate from the comfort of your home.

• Flexible working hours with minimal meetings and no strict 9-5 schedule.

• Comprehensive health and dental coverage.

• Parental leave top-ups in addition to Employment Insurance (EI) benefits.

• Unlimited vacation/PTO.

• Emphasis on work-life balance.