Machine Learning Operations Engineer – MLOps

Job not on LinkedIn

🔥 1 hour ago

💃 Latin America – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 15%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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CodeRoad

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1 - 10 employees

📚 Education

☁️ SaaS

Education • SaaS

CodeRoad is a comprehensive online training program that teaches JavaScript and front-end web development from zero to a Junior Front-End Developer level. Created and taught by Mateusz Choma, the course includes 175+ hours of video lessons, hands-on code examples in an in-browser editor, and covers HTML, CSS, JavaScript, React and Redux, plus community Q&A and optional one-on-one mentoring. The platform is self-paced and accessible 24/7, aimed at individuals seeking to start a career in front-end development.

📋 Description

• 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

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