AI DevOps Engineer

AI DevOps Engineer

Chopping Block AI is seeking an experienced AI DevOps Engineer to join our growing team building and maintaining machine learning pipelines in cloud environments. In this role, you will design, implement, and optimize CI/CD workflows specifically tailored for AI/ML model training, validation, and deployment. You’ll work closely with data scientists, ML engineers, and software engineers to ensure reliable, scalable, and reproducible model delivery.

Key Responsibilities

• Architect and maintain cloud-native ML pipelines using tools like Kubeflow, MLflow, Airflow, or custom solutions.
• Implement robust CI/CD pipelines for model training, testing, and deployment across multiple environments (dev, staging, production).
• Automate infrastructure provisioning with Terraform, CloudFormation, or Pulumi on AWS, GCP, or Azure.
• Monitor and optimize GPU/TPU resource utilization, cost, and performance for large-scale training jobs.
• Establish best practices for model versioning, artifact management, and rollback strategies.
• Collaborate with security teams to enforce compliance, secrets management, and data privacy in ML workflows.
• Develop internal tooling and self-service platforms to accelerate ML experimentation and productionization.

Why Join Us?

• Work at the intersection of DevOps and cutting-edge AI research.
• Competitive salary range: $77,600 – $176,000 (based on experience and location).
• Flexible remote work policy with optional office hubs.
• Comprehensive benefits including health, dental, vision, 401(k) matching, and professional development budget.
• Opportunity to shape the ML infrastructure strategy for a fast-growing AI company.

If you are passionate about automating the ML lifecycle and thrive in a collaborative, high-impact environment, we’d love to hear from you.

• 3+ years of DevOps/SRE experience with a focus on ML/AI workloads
• Proficiency with container orchestration (Kubernetes, Docker) and GPU scheduling
• Strong scripting skills in Python, Bash, or Go
• Hands-on experience with CI/CD tools (GitHub Actions, GitLab CI, Jenkins, Argo CD)
• Deep knowledge of at least one major cloud provider (AWS, GCP, Azure) and infrastructure-as-code
• Familiarity with ML frameworks (PyTorch, TensorFlow, JAX) and model serving (Triton, TorchServe, BentoML)
• Experience with MLOps tools (MLflow, Weights & Biases, ClearML, Kubeflow) is a plus
• Excellent communication and documentation skills
• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience