AI/ML Ops Engineer
CA$131,000 – CA$164,500 / yr base salary
Posted 17 Aug 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- Remote
- Contract
- Full-time
| Base salary | CA$131,000 – CA$164,500 / yr |
|---|
Blackpoint Cyber is the leading provider of world-class cybersecurity threat hunting, detection and remediation technology. Founded by former National Security Agency (NSA) cyber operations experts who applied their learnings to bring national security-grade technology solutions to commercial customers around the world, Blackpoint Cyber is in hyper-growth mode, fueled by a recent $190m series C round.
ROLE SUMMARY
As AI/ML Ops Engineer, you will own the operational backbone of Blackpoint's AI/ML capability — taking models from training through production deployment and owning the full AI/ML loop across every pipeline the team runs at scale. You will be instrumental in building out this new function: standing up deployment pipelines, taking trained scripts and putting them on endpoints that can accept live requests, and ensuring every solution you ship is production-grade, highly available, and well monitored. As the team's scope expands, you will take on ownership of testing across the board and automate training, monitoring, and deployment pipelines across the AI lifecycle. You will report to the Vice President of AI and Data and work closely with Engineering, the Security Operations Center (SOC), and the Adversary Pursuit Group (APG).
WHO YOU ARE
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5+ years of hands-on ML Engineering experience, including having personally trained and deployed models into a production environment — you know what it takes to take an AI product from prototype to live service.
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A well-architected mindset — built for efficiency, performance, security, and reliability, with genuine comfort owning deployment pipelines end-to-end.
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Strong analytical and problem-solving abilities, with a focus on data-driven decision-making.
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Excellent communication and interpersonal skills, with the ability to influence and collaborate with stakeholders at all levels.
WHAT YOU'LL BRING
Experienced in:
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Cloud-based ML Infrastructure (AWS)
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Model Development, Evaluation, & Deployment Operations (SageMaker, Bedrock)
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Inference Streams & Event-Driven Processing (Kafka, Spark)
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MLOps Workflows (MLFlow, Sagemaker Pipelines)
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Infrastructure as Code & Pipeline Automation (Terraform, AI CI/CD, GitHub Actions)
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ML Governance (Data, Model, & Feature Versioning, Monitoring & Testing)
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Containerized Services (Docker, Kubernetes, ECS/EKS)