{"id":1114020,"url":"https://alion.io/job/point-click-care-senior-machine-learning-systems-engineer-cad","title":"Senior Machine Learning Systems Engineer (CAD)","company":{"id":3321,"name":"PointClickCare","domain":"pointclickcare.com","url":"https://alion.io/company/point-click-care","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":83,"open_postings":10,"ghost_share":0,"stale_share":0.7,"repost_share":0,"time_to_fill_p50_days":59,"computed_at":"2026-11-09T06:03:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mississauga, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":174000,"max":218000,"currency":"CAD","period":"year","gross":null,"usd_annual":155240},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Docker","optional":false},{"name":"Feature Store","optional":false},{"name":"GCP","optional":false},{"name":"Java","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Python","optional":false},{"name":"Ray","optional":false}],"status":"live","first_seen_at":"2026-09-22T12:55:14Z","employer_posted_date":"2026-09-22","last_verified_at":"2026-11-10T04:54:28Z","board_verified":true,"closed_at":null,"days_open":48,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":48},"description":"Team Summary\nThis team will serve as the product owner for the machine learning platform capabilities within PointClickCare, working closely with other engineering teams across the organization to identify, build and support traditional machine learning (ML) and hybrid ML/LLMsolutions. This centralized team with deep specialization will closely integrate with key horizontal partners to ensure delivery of safe, scalable, and high-impact AI products.\nJob Summary\nThe Senior Machine Learning Systems Engineer will work closely with the Product and Engineering teams to design, build, and operate the machine learning platform that enables teams across PointClickCare to develop, deploy, and scale ML solutions. The Senior AI Machine Learning Systems Engineer will also build and maintain the pipelines, tooling and infrastructure for model training, deployment, serving, and monitoring that underpin our AI products.\nKey Responsibilities\nCollaborate with product and engineering teams to translate ML needs into reliable, reusable platform capabilities.\nDesign and build scalable data and ML pipelines that support model training, evaluation, deployment, and serving.\nDevelop and maintain ML Ops tooling and workflows, including CI/CD for models, model registry, feature stores, and experiment tracking.\nEnsure the reliability, observability, and performance of ML systems in production through monitoring, alerting, and automated remediation.\nImplement comprehensive security mechanisms for the ML platform, including authentication, role-based access control, audit logging, and compliance monitoring.\nSecurely integrate the platform with existing systems, APIs, and data sources with secure communication protocols, and optimize infrastructure for cost, performance, and scale.\nMentor engineers on the teams and promote reusable platform patterns and best practices.\nQualifications & Skills\nExpert level in Python and Java, and strong software engineering fundamentals.\nExperience designing and building ML platforms and MLOps workflows, with familiarity with tools such as MLflow, Kubeflow, Ray, and model-serving frameworks.\nExperience with cloud platforms (Primarily Azure, secondarily AWS and GCP)\nExperience with ML runtime containerization, optimization, and orchestration (Docker, Kubernetes).\nPreferred\nBachelor’s degree or higher in Computer Science, Machine Learning, or a related field.\nWorking familiarity with Azure Machine Learning components and Databricks processing and serverless environments\nExperience implementing security at scale including role-based access control, multi-factor authentication, network security best practices, and compliance monitoring.\nExperience optimizing large model training and inference (including LLM serving) for performance and cost.","description_format":"text","description_chars":2789,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Canada","iso":"CA","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["EHR & Clinical Software"],"lifecycle":[{"event":"open","at":"2026-09-22T14:01:11Z"}],"visa":[],"liveness":{"score":45,"band":"ok","label":"Likely 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