Principal ML Architect – Open Internet

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🔥 30 minutes ago

🇨🇦 Canada – Remote

💵 CA$280k - CA$350k / year

⏰ Full Time

⚪️ Entry-level

🏛️ Architect

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Lutra.

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2006

☁️ SaaS

💼 Consulting

🤝 B2B

💰 $56.7k Grant on 2017-03

SaaS • Consulting • B2B

Lutra is a New Zealand–headquartered engineering and software company focused on water and wastewater treatment. It provides process engineering, optimisation, commissioning support, investigations and training for water and wastewater plants, and develops operations-management software (branded Infrastructure Data / ID) including scheduling and digital forms to help utilities manage compliance, inspections and data. Lutra also produces technical content (videos, case studies) and is exploring AI applications to accelerate its offerings. It serves councils and utilities across New Zealand and Australia and offers both project services and ongoing software solutions.

📋 Description

• Design and evolve end-to-end architectures for large-scale machine learning systems • Design solutions for validating, transforming and generating features from extremely large datasets • Architect reliable model delivery from development into production • Develop approaches for deploying, hosting and operating ML models at scale • Establish approaches for managing and monitoring deployed models and supporting systems • Optimize ML system performance across data processing, model execution and serving infrastructure • Lead functional and process design across ML initiatives, including scenario design, flow mapping, prototyping, testing and support procedures • Apply software engineering principles to create maintainable, production-grade ML systems • Collaborate with data science, machine learning, software engineering and other stakeholders • Provide architectural direction and influence the organization’s machine learning approach

🎯 Requirements

• Masters or PhD in a STEM field or equivalent depth of experience • Understanding of operating ML reliably in production • Extensive knowledge of MLOps infrastructure and pipelines • Meaningful experience across classification, regression, pattern recognition, recommendation systems, targeting systems or ranking systems • Deep knowledge of mathematics, probability, statistics and algorithms • Understanding of data preparation, feature generation, model delivery, deployment, monitoring and operational support • Interest in performance optimization and reasoning about large-scale ML trade-offs • Understanding of software engineering best practices • Strong business acumen and cross-functional capability • Principal-level experience defining architecture, navigating ambiguity and influencing technical direction • Software engineering background in addition to machine learning expertise is a bonus • Experience deploying ML models for rapid/real-time inference is a bonus • Published ML, statistics, optimization or adjacent-field articles, research or papers are a bonus • Experience designing ML systems under enormous data volumes, high transaction throughput and tight latency constraints is a bonus

🏖️ Benefits

• RRSP matching • Career stability and longevity • Infrastructure and systems designed for reliability and efficiency

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