Senior Software Engineer, Machine Learning

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

📋 Description

• Conceptualize and oversee a cloud-native big data platform that manages audience information for millions of participants and billions of interactions each year.

• Architect and manage machine learning infrastructure, including feature stores, training pipelines, model deployment, and monitoring.

• Guarantee dependable, low-latency access to features and machine learning infrastructure.

• Take ownership of the entire data pipeline, from change data capture through validation, transformation, and denormalization.

• Relate data-system performance and reliability to customer satisfaction and business results.

• Develop data products with established service-level agreements (SLAs), robust data integrity, and ease of discovery.

• Utilize AI coding assistants such as Claude Code.

• Construct LLM-powered pipelines and autonomous agents to enhance, classify, and act upon audience data at scale.

• Collaborate with product and engineering teams while effectively communicating technical choices to stakeholders.

⛳️ Requirements

• Over 8 years of practical experience in data engineering.

• Demonstrated success in designing, constructing, and operating large-scale distributed data and machine learning systems in production environments.

• Strong understanding of core machine learning concepts, including supervised/unsupervised learning, cross-validation, bias–variance tradeoff, regularization, evaluation metrics, regression, tree ensembles, and clustering.

• Experience in feature engineering using Python ML tools, such as pandas and scikit-learn; familiarity with PyTorch or TensorFlow is a plus.

• Hands-on experience with production machine learning pipelines and feature datasets for model training and inference.

• Knowledge of MLOps practices such as experiment tracking, model versioning/registry, deployment, and monitoring for drift/data quality.

• Solid foundations in distributed systems, including partitioning strategies, consistency models, backpressure management, fault tolerance, and capacity planning.

• Experience implementing LLMs and agentic systems in real-world data or ML applications.

• Product and commercial mindset with the capability to present technical decisions in relation to customer impact and business outcomes.

• Excellent communication skills for interacting with non-technical stakeholders.

• Proficiency in programming with Python and Django.

• Familiarity with databases such as Clickhouse, MySQL, MongoDB, ElasticSearch, and Redshift.

• Experience using workflow management tools like Airflow or Dagster.

• Comfortable working independently in dynamic and uncertain environments.

• Proficient in diagnosing and resolving complex machine learning system issues.

• Nice to have: experience in taking ownership of or re-architecting a data platform from start to finish.

• Nice to have: background in SaaS or event-driven product development.

🏝️ Benefits

• Competitive salary and equity options.

• Fully remote work from the comfort of your home.

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

• Health & Dental benefits with parental leave top-ups in addition to Employment Insurance (EI) benefits.

• Unlimited vacation/PTO.