MLOps Engineer

Meet Benevity

Benevity is the way the world does good providing companies (and their employees) with technology to take social action on the issues they care about. Through giving volunteering grantmaking employee resource groups and microactions we help most of the Fortune 100 brands build better cultures and use their power for good. Were also one of the first B Corporations in Canada meaning were as committed to purpose as we are to profits. We have people working all over the world including Canada Spain Switzerland the United Kingdom the United States and more!

Were seeking an experienced MLOps Engineer to lead operational excellence and infrastructure development within our AI team focusing on the full machine learning lifecycle across classical ML and deep learning systems. Youll be instrumental in designing deploying and managing scalable ML pipelines and platforms in our B2B SaaS environment ensuring that our ML services are productionready secure reliable and observable.

This role operates within a Scrum team and involves close collaboration with ML researchers data scientists platform engineers and DevOps teams to build robust ML solutions integrated into Benevitys product ecosystem.

What youll do:

ML/AI Platform Engineering & Operations

• Design and manage cloudnative infrastructure for ML model training evaluation deployment and monitoring on platforms like Azure ML SageMaker Vertex AI or Databricks.
• Build and maintain InfrastructureasCode (IaC) using tools such as Terraform to support reproducible scalable and auditable ML deployments.
• Develop endtoend MLOps pipelines supporting continuous integration and delivery (CI/CD) model versioning automated testing and retraining workflows.
• Implement observability practices including logging monitoring and alerting to ensure model and system performance in production.
• Optimize infrastructure for costefficiency model latency throughput and reliability.
• Ensure security of ML pipelines and services through authentication authorization ratelimiting and auditing mechanisms.

Operational Excellence & Observability

• Instrument ML systems with metrics traces logs and dashboards to support performance monitoring and issue detection.
• Participate in incident management including oncall rotations writing operational runbooks and conducting postmortems to drive continuous improvement.
• Apply security and compliance best practices to data handling model outputs and system operations aligning with regulatory standards.

Integration & Collaboration

• Work closely with data scientists to move models from experimentation to production.
• Collaborate with software engineers to integrate ML capabilities into core products such as recommendation engines personalization or predictive analytics.
• Partner with DevOps Security and SRE teams to maintain compliance (e.g. SOC2 GDPR) and platform readiness.
• Engage in architectural reviews and contribute to design decisions around machine learning infrastructure and APIs.

Scrum Delivery & Continuous Improvement

• Actively participate in scrum ceremonies including sprint planning standups and retrospectives.
• Provide effort estimates contribute to backlog grooming and deliver quality features and improvements in a continuous delivery cycle.
• Maintain clear documentation of ML infrastructure processes and decisions for transparency and collaboration.

Innovation & Learning

• Stay current with advancements in GenAI infrastructure large language models and emerging patterns like RetrievalAugmented Generation (RAG) vector search and agentbased architectures.
• Stay informed about emerging trends in MLOps model deployment monitoring and datacentric AI practices.
• Contribute to the evaluation and benchmarking of deployed models for accuracy fairness and efficiency.
• Share insights tools and methodologies to support the broader AI/ML engineering community at Benevity.

What youll bring:

• A degree in Computer Science Engineering or a related field.
• 3 years of experience in DevOps MLOps or SRE roles with handson responsibility for ML model deployment and lifecycle management.
• Experience with cloud ML platforms such as AWS SageMaker GCP Vertex AI Azure ML or Databricks.
• Proficiency in IaC tools (Terraform CloudFormation) and workflow orchestration (Airflow Kubeflow or MLflow).
• Strong Python skills for scripting automation and interaction with ML APIs and orchestration tools.
• Familiarity with observability tools like Prometheus Grafana Datadog or cloudnative monitoring (CloudWatch GCP Monitoring Azure Monitor).
• Experience implementing CI/CD pipelines for ML using GitHub Actions Jenkins ArgoCD or similar.
• Solid understanding of data security model governance and compliance in the context of ML systems.
• Ability to diagnose complex issues across infrastructure models and data flows.
• Excellent communication skills and a collaborative mindset to work crossfunctionally in scrum teams.

Technical Skills & Expertise:

• Cloud Platforms: Azure ML GCP Vertex AI AWS SageMaker Databricks
• MLOps Tooling: MLflow Kubeflow Pipelines Airflow TFX DVC Docker Kubernetes Triton Inference Server
• CI/CD & Infrastructure: Terraform GitHub Actions Jenkins ArgoCD GitOps
• Monitoring & Observability: Prometheus Grafana OpenTelemetry Datadog cloudnative monitoring tools
• Languages: Python (primary) Bash. Bonus: Go Rust or Java for backend systems
• APIs & Streaming: REST gRPC Kafka Pub/Sub Kinesis
• Security & Compliance: IAM Kubernetes RBAC audit logging TLS/SSL VPC configurations KMS OPA and compliance standards like SOC2 GDPR and HIPAA

Discover your purpose at work

Were not employees were Benevityites. From all locations backgrounds and walks of life who deserve more

Innovative work. Growth opportunities. Caring coworkers. And a chance to do work that fills us with a sense of purpose.

If the idea of working on tech that helps people do good in the world lights you up ... If you want a career where youre valued for who you are and challenged to see who you can become

Its time to join Benevity. Were so excited to meet you.

Where we work

At Benevity we embrace a flexible hybrid approach to where we work that empowers our people in a way that supports great work strong relationships and personal wellbeing. For those located near one of our offices while theres no set requirement for inoffice time we do value the moments when coming together in person helps us build connection and collaboration. Whether its for onboarding project work or a chance to align and bond as a team we trust our people to make thoughtful decisions about when showing up in person matters most.

Join a company where DEIB isnt a buzzword

Diversity equity inclusion and belonging are part of Benevitys DNA. Youll see the impact of our massive investment in DEIB daily from our wellsupported employee resources groups to the exceptional diversity on our leadership and tech teams.

We know that diverse backgrounds experiences skills and passions are what move our business and our people forward so were committed to creating a culture of belonging with equal opportunities for everyone to shine.

That starts with a fair and accessible hiring process. If you want to feel seen heard and celebrated you belong at Benevity.

Candidates with disabilities who may require accommodations throughout the hiring or assessment process are encouraged to reach out to .