Propio is looking to design, build, and maintain the production infrastructure required to deploy, scale, monitor, and govern ML and agentic AI systems to enhance interpreter workflows, automate multilingual insights, and scale communication quality across industries.
Requirements
- Strong experience with AWS (SageMaker, EKS/ECS, Lambda, Step Functions, S3, IAM), Databricks, or equivalent cloud ecosystems
- Strong proficiency with ML lifecycle tools: MLflow, Kubeflow, SageMaker Pipelines, Airflow, Prefect, or equivalent
- Strong foundations in CI/CD, containerization (Docker), orchestration (Kubernetes), and infrastructure-as-code (Terraform, CloudFormation)
- Experience implementing monitoring and observability for ML systems (Datadog, Prometheus/Grafana, LangSmith, MLflow)
- Familiarity with securing ML pipelines and handling regulated data under HIPAA and SOC2
- Proficiency in Python and experience supporting ML engineers in productionizing ML/LLM workflows
- Experience with GPU/compute orchestration strategies for cost-efficient workloads
Responsibilities
- Build and maintain scalable model serving infrastructure for real-time inference (translation, ASR/TTS, agentic AI workflows)
- Implement automated CI/CD pipelines for ML models and LLM agents, including versioning, rollback strategies, and multi-environment promotion (dev ? staging ? prod)
- Develop GPU/compute orchestration strategies for cost-efficient workloads across AWS (SageMaker, ECS/EKS, EC2, or Databricks)
- Implement reproducible ML workflows with strong dependency management, data lineage, feature versioning, and reproducibility guarantees
- Integrate observability platforms (Datadog, MLflow, LangSmith) for end-to-end tracing of agentic workflows and multi-step tool execution
- Build alerting systems and dashboards for both business-level metrics (quality, throughput) and engineering metrics (GPU load, memory, queue depth
- Ensure ML systems meet HIPAA, SOC2, and HITRUST standards, including encryption, audit logging, access controls, and secure handling of PHI
Other
- 3+ years of experience in ML Olps, DevOps, or ML platform Engineering or similar infrastructure-focused ML roles
- Bachelor’s or Master’s in Computer Science, Software Engineering, ML/AI, or related field
- Work closely with Machine Learning Engineers to productionize models and agentic systems, ensuring seamless handoff from experimentation to deployment
- Collaborate with Data Engineering to operationalize data pipelines feeding ML/LLM workflows
- Partner with DevOps, Security Engineering, and Platform Engineering to integrate ML systems into Propio’s cloud stack
