Machine Learning Operations Engineer – MLOps

This is a fully remote position, open to applicants in Latin America.

📋 Description

• Design, implement, and oversee scalable, production-quality deployment pipelines for autonomous AI models and multi-agent workflows utilizing LangGraph, CrewAI, and n8n.

• Construct and sustain robust multi-cloud AI infrastructure on GCP or AWS.

• Create automated CI/CD and Continuous Training pipelines leveraging Git, Docker, and Kubernetes.

• Develop observability frameworks with Langtrace, AgentOps, Prometheus, CloudWatch, and Grafana.

• Monitor model drift, latency, and the accuracy of autonomous decisions in real-time.

• Establish security architectures that include IAM, data encryption, prompt injection defense, and automated GDPR safety measures.

• Set data quality standards, version control, and ethical AI protections.

• Collaborate with cross-functional AI teams throughout the operational lifecycle.

⛳️ Requirements

• Minimum of 4 years of professional experience in MLOps or DevOps.

• At least 1 year dedicated to deploying, evaluating, and managing production AI/ML models and agentic workflows.

• Extensive hands-on experience with GCP (Vertex AI, Cloud Storage, BigQuery, Cloud Functions) or AWS (SageMaker, S3, Redshift, Lambda).

• Proficient in Python, Bash, Terraform, Docker, Kubernetes, and AI/ML orchestration tools (PyTorch, LangGraph, CrewAI, n8n).

• Practical expertise in monitoring LLM execution, tracking data drift, and ensuring system health using tools such as Langtrace, AgentOps, Prometheus, or CloudWatch.

• Strong understanding of cloud security protocols (IAM, data privacy) and ethical AI principles (bias detection, explainability, compliance).

• Advanced English proficiency, both written and spoken, is essential 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 collaborate with high-growth U.S.-based companies and cutting-edge technology stacks.

• Access to agentic AI tools and training.

• Coursera Enterprise.

• Studio practice labs.

• L1-L7 Career Framework.

• Comprehensive onboarding process.

• Open leadership communication.

• Community recognition initiatives.

• Emphasis on psychological safety.

• Continuous multi-project pipeline engagement.

• Direct involvement with U.S. client teams and their roadmaps.