Machine Learning Operations Engineer – MLOps

Posted 2hrs ago

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Job Description

MLOps Engineer deploying agentic AI pipelines and multi-cloud infrastructure. Supporting CodeRoad’s technology execution projects for high-growth U.S.-based companies.

Responsibilities:

  • Design, deploy, and manage scalable, production-grade deployment pipelines for autonomous AI models and multi-agent workflows using LangGraph, CrewAI, and n8n
  • Build and maintain resilient multi-cloud AI infrastructure on GCP or AWS
  • Establish automated CI/CD and Continuous Training pipelines using Git, Docker, and Kubernetes
  • Implement observability frameworks using Langtrace, AgentOps, Prometheus, CloudWatch, and Grafana
  • Track model drift, latency, and autonomous decision accuracy in real time
  • Implement security architectures including IAM, data encryption, prompt injection defense, and automated GDPR safety guardrails
  • Establish data quality standards, version control, and ethical AI safeguards
  • Collaborate with cross-functional AI teams across the operational lifecycle

Requirements:

  • 4+ years of professional experience in MLOps or DevOps
  • 1+ year dedicated to deploying, evaluating, and managing production AI/ML models and agentic workflows
  • Deep hands-on experience with GCP (Vertex AI, Cloud Storage, BigQuery, Cloud Functions) or AWS (SageMaker, S3, Redshift, Lambda)
  • Proficiency in Python, Bash, Terraform, Docker, Kubernetes, and AI/ML orchestration tools (PyTorch, LangGraph, CrewAI, n8n)
  • Hands-on expertise monitoring LLM execution, tracking data drift, and maintaining system health using tools like Langtrace, AgentOps, Prometheus, or CloudWatch
  • Solid understanding of cloud security protocols (IAM, data privacy) and ethical AI principles (bias detection, explainability, compliance)
  • Advanced English skills, written and spoken, mandatory for collaboration with U.S.-based teams across East/West Coast time zones

Benefits:

  • Competitive Pay (USD)
  • Holidays Off & Paid Time Off
  • Health insurance assistance program
  • 100% Remote
  • Opportunity to work with high-growth US-based companies and cutting-edge tech stacks
  • Agentic AI tools and training
  • Coursera Enterprise
  • Studio practice labs
  • L1-L7 Career Framework
  • High-touch onboarding
  • Transparent leadership communication
  • Community recognition
  • Psychological safety
  • Continuous multi-project pipeline
  • Direct engagement with U.S. client teams and roadmaps