Principal ML System Engineer

🕒 August 13

🇨🇦 Canada – Remote

💵 $176k - $195k / year

⏰ Full Time

🔴 Lead

⚙️ Systems Engineer

👻 Ghost score 11%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.Why this score:

• Open for 91 days.
• Jobs at this company usually fill in 48 days.

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PointClickCare

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🏥 Healthcare

💼 Consulting

⚕️ Healthcare Insurance

💰 Secondary Market on 2022-03

Healthcare • Consulting • Healthcare Insurance

PointClickCare is a cloud-based software provider focused on improving care collaboration and financial health in the healthcare industry. The company offers a comprehensive platform that connects care teams with important data, allowing for seamless care transitions and better patient outcomes. By streamlining operations for skilled nursing facilities, senior living communities, and other healthcare providers, PointClickCare helps reduce inefficiencies, manage medication orders, ensure compliance, and improve financial performance. PointClickCare also fosters innovation and quality improvements in healthcare through integrated care coordination and actionable insights across data silos.

📋 Description

• Serve as the product owner for GenAI capabilities within PointClickCare • Work with engineering teams to identify, build, and support generative AI solutions • Design, build, and maintain core infrastructure for GenAI products, including model gateways, prompt/versioning stores, vector databases, and LLM evaluation tools • Implement secure access controls and authentication mechanisms in AI platform components • Develop and manage observability, monitoring, and logging for GenAI workloads and infrastructure • Integrate GenAI infrastructure with agent frameworks and downstream applications • Optimize infrastructure for scalability, high availability, and cost efficiency in production workloads

🎯 Requirements

• Extensive experience building and maintaining AI platform infrastructure • Experience with Kubernetes and container security • Expertise in observability and monitoring frameworks focused on real-time performance • Experience with OpenTelemetry and NLPFlow • Experience with vector databases, prompt/versioning stores, and AI IDEs • Familiarity with vLLM, SGLang, or similar frameworks for hosting LLM inference workloads • Experience with CI/CD pipelines and automation for AI model deployment and platform operations • Strong knowledge of authentication and authorization frameworks integrated into AI platforms

🏖️ Benefits

• Bonus • Benefits • Total rewards package

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