Job Specifications
Our mission at Greenhouse is to make every company great at hiring – so we go to great lengths to hire great people because we believe that they’re the foundation of our success. At Greenhouse, you’ll join a team that collaborates purposefully, fosters inclusivity, and communicates with transparency and accountability so we can help companies measurably improve the way they hire.
Join us to do the best work of your career, solving meaningful problems with remarkable teams.
Greenhouse is looking for a Senior ML Ops Engineer to join our team!
As a senior member of our Applied Machine Learning team, you'll own the critical infrastructure and processes that bring our machine learning models to life. You will be responsible for the full model lifecycle, from working with prototypes of ML and LLM-based solutions to transforming them into reliable, production-ready systems. You'll create, manage, and improve our continuous integration and delivery pipelines that enable rapid iteration and deployment.
Learn more about our engineering culture here!
Who Will Love This Job
An ML Evangelist– You stay in the know of ML industry trends and enable your team’s ability to work with ML tools.
An Architect – You excel at creating, managing, and improving robust continuous integration and delivery pipelines to support rapid deployment of ML models.
A Reliability Advocate – You are passionate about system uptime, implementing observability practices like monitoring, logging, and alerting, and ensuring high data quality and performance in production.
A Collaborator – You excel at working closely with others across an org to align on requirements and deliver solutions.
What You'll Do
Operationalize ML and LLM-based workloads, gather stakeholder feedback, and drive them into production-ready systems
Create, manage, and improve continuous integration and delivery pipelines to support rapid iteration and deployment of ML models and services
Implement observability practices for ML systems, including monitoring, logging, and alerting
Maintain and improve the infrastructure for ML/LLM evaluation sets, including versioning, automated validation pipelines, and continuous quality checks across the model lifecycle
Ensure high data quality and monitor performance of ML workloads in production
Work closely with ML engineers, data scientists, and cross-functional teams to build impactful solutions
Participate in an on-call rotation to ensure system uptime and reliability
Additional projects and responsibilities as business needs require
You should have
Proven experience in an MLOps, DevOps, or a related software engineering field
Experience implementing safe, ethical, and compliant ML systems (familiarity with ISO 42001/NIST AI RMF and the associated common controls)
Strong cloud infrastructure experience with AWS
A deep understanding of Kubernetes
Expertise with IaC (Infrastructure as Code) & GitOps Tools like Terraform and Argo CD
Experience developing and augmenting CI/CD Pipelines
A strong understanding of the state of the art in machine learning, especially LLMs
Familiarity with ML frameworks such as PyTorch, MLFlow, vLLM, Transformers, and Torch
Practical experience managing data quality and performance in production ML environments
Experience designing data architectures optimized for AI/ML, such as with Opensearch (vector databases)
Familiarity with tools and platforms like Bedrock/Sagemaker, MetaFlow, Databricks, Vertex AI, Skypilot, Kubeflow, Loki, or Grafana is a plus
Your own unique talents! If you don't meet 100% of the qualifications outlined above, tell us why you'd be a great fit for this role in your cover letter.
Applicants must be legally eligible to work in Canada as of the start date chosen by the Company. We are unable to support sponsorship at this time.
For purposes of processing or administering your employment relationship, personal information that you provide to the Company may be transferred to and accessed by an affiliate in the United States or elsewhere, or to agents and contractors (such as payroll companies, insurance companies, information technology consultants, etc.) that provide services to the Company.
The national pay range for this role is $143,000 - $214,000 CAD. Individual compensation will be commensurate with the candidate's experience and qualifications. Certain roles may be eligible for additional compensation, including stock option awards, bonuses, and merit increases. Additionally, certain roles have the opportunity to receive sales commissions that are based on the terms of the sales commission plan applicable to the role.
The anticipated closing date for this role is December 12th, 2025.
This hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making.
Who We Are
At Greenhouse, we live by our mission through using our own product to help us hire the right p
About the Company
Greenhouse is the all-together hiring platform, giving companies of all sizes everything they need to hire better. Our software provides comprehensive solutions – from sourcing to onboarding – that seamlessly support collaborative decision-making, more fair and equitable hiring and, ultimately, business growth. We’ve helped over 7,500 companies across diverse industry verticals, like Trivago, HubSpot, DoorDash, SeatGeek and Lyft, make hiring their strategic advantage. With our structured hiring approach, complete suite of so...
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