Senior ML Ops Engineer

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 currently authorized to work in the United States on a full-time basis.

If you are based in California, we encourage you to read this important information for California residents linked here.

The national pay range for this role is $153,000- $215,000. 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.

Greenhouse provides a variety of benefits to employees, including medical, dental, and vision insurance, basic life insurance, mental health resources, financial wellness benefits, and a fully paid parental leave program. For US-based employees, we offer short-term and long-term disability coverage, a 401(k) plan and company match. U.S. based employees also receive, per calendar year, up to 14 scheduled paid holidays and up to 80 hours of paid sick leave. Non-exempt employees accrue up to 20-25 days of paid vacation time annually, depending on tenure, and exempt employees have flexible paid time off (PTO).

The anticipated closing date for this role is February 16th, 2026.

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.