DevOps Engineer

4 days ago

Cary, North Carolina, United States Hire Orbitt Full time $120,000 - $160,000 per year

DevOps Engineer - GCP / Machine Learning

We are seeking a skilled DevOps Engineer with deep expertise in Google Cloud Platform (GCP) to help us build a world-class machine learning and AI capabilities within the bank. You will be instrumental in designing, implementing, and maintaining scalable infrastructure and automated pipelines that support the full machine learning lifecycle—from experimentation to deployment and monitoring.

This role involves close collaboration with data scientists, data engineers, product managers, and platform teams to operationalize models, streamline workflows, and uphold the highest standards of security, privacy, and compliance. You'll help define and evolve our MLOps practices, ensuring our AI solutions are reliable, reproducible, and impactful.

Key Responsibilities

  • Build and maintain CI/CD pipelines for ML workflows using GCP-native tools such as Cloud Build, Artifact Registry, and Cloud Deploy.
  • Containerize and orchestrate ML workloads using Docker, Kubernetes, and GKE (Google Kubernetes Engine).
  • Collaborate with cross-functional teams to transition models from development to production, integrating them into customer-facing applications.
  • Implement robust model monitoring, logging, and alerting using tools like Vertex AI Model Monitoring, Cloud Logging, and Cloud Monitoring.
  • Define and enforce best practices for model versioning, testing, and reproducibility using tools like MLflow and Vertex AI Pipelines.
  • Ensure infrastructure adheres to security and compliance standards, working closely with Cybersecurity and Data Governance teams.
  • Continuously evaluate and integrate emerging GCP technologies to enhance platform capabilities and delivery speed.

Required Skills & Experience

  • Bachelor's degree in Computer Science, Software Engineering, or related field.
  • 5+ years of experience in MLOps or DevOps roles, with a strong focus on cloud-native ML infrastructure.
  • Proven experience deploying ML models in production (batch and real-time), ideally in regulated or privacy-sensitive environments.
  • Proficiency in Python, with solid software engineering fundamentals and experience using Terraform or Deployment Manager for infrastructure-as-code.
  • Hands-on experience with:
  • GCP ML tools: Vertex AI, AI Platform, BigQuery ML
  • CI/CD: Cloud Build, GitHub Actions, Jenkins
  • Containerization & Orchestration: Docker, Kubernetes, GKE

Preferred Qualifications

  • Experience deploying and managing generative AI models (LLMs) in production, including prompt engineering, evaluation pipelines, and safety guardrails.
  • Familiarity with observability tools such as MLflow, LangFuse, or Braintrust.
  • Exposure to data governance and privacy frameworks in cloud environments.

Job Types: Full-time, Contract

Pay: $100, $140,000.00 per year

Benefits:

  • 401(k)
  • Dental insurance
  • Health insurance
  • Paid time off
  • Vision insurance

Work Location: Hybrid remote in Cary, NC 27513

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