Senior MLOps Engineer (AI)

TL;DR

Senior MLOps Engineer (AI/MLOps): Designing and implementing infrastructure and tooling for the development, deployment, and iteration of machine learning models and AI agents with an accent on scalability, reliability, and AI platform establishment. Focus on building CI/CD pipelines for AI workflows, optimizing model serving infrastructure, and implementing model governance and observability.

Location: Remote (Must be based in one of the 32 approved US states)

Salary: $190,000 - 220,000

Company

hirify.global is bridging the gap between education and career opportunity through a Career Opportunity Platform that helps employers offer education and skilling to their employees.

What you will do

• Design, implement, and maintain platforms for seamless deployment, management, and monitoring of ML models and AI agents.
• Develop and optimize CI/CD pipelines specifically tailored for AI and machine learning workflows.
• Collaborate with data scientists, software engineers, and product teams to streamline ML model productionization.
• Ensure infrastructure is scalable, secure, and adheres to best practices in reliability and observability.
• Provide technical leadership in adopting best practices for model governance, versioning, testing, and validation.
• Mentor team members on MLOps standards, practices, and emerging technologies.

Requirements

• 5–7 years of experience in MLOps, DevOps, software engineering, or related fields.
• Expertise with cloud platforms (AWS, Azure, or GCP), particularly managed AI/ML services.
• Proficiency with containerization (Docker, Kubernetes) and orchestration tools.
• Experience in model deployment frameworks and serving infrastructure (TensorFlow Serving, TorchServe, FastAPI, etc.).
• Skilled in infrastructure-as-code (Terraform) and CI/CD automation (GitHub Actions, Jenkins).
• Must be able to live and work full-time in one of the approved 32 US states.

Nice to have

• Experience in MCP (model context protocol), specifically with Databricks MCP or AWS MCP.
• Deep understanding of experiment tracking tools like MLflow, Kubeflow, or Weights & Biases.

Culture & Benefits

• Comprehensive health care options through Collective Health and Kaiser.
• 401k retirement savings plan.
• Vacation policy and 8 days of fully-paid sick leave.
• Generous parental leave (12 weeks for non-birthing, 18-20 weeks for birthing parents).
• Mental health resources and financial wellbeing support services.
• Education benefits and tuition assistance for professional growth.