DevOps Engineer

We’re looking for an experienced MLOps / DevOps Engineer to build and maintain the production infrastructure powering our ML systems. You’ll ensure reliability, scalability, and automation of model pipelines, CI/CD workflows, and cloud infrastructure.

Responsibilities

• Build and maintain CI/CD pipelines for ML training, validation, and deployment

• Manage AWS infrastructure (SageMaker, ECS/EKS, Lambda, S3)

• Deploy and scale ML model serving and inference services

• Containerize services with Docker and manage Kubernetes environments

• Implement monitoring, logging, and alerting (Prometheus, Grafana, CloudWatch)

• Manage infrastructure with Terraform / IaC

Requirements

• 6+ years in DevOps, SRE, or MLOps

• Strong experience with AWS cloud infrastructure

• Production experience with Docker and Kubernetes

• Experience with CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI, etc.)

• Strong Python scripting and automation skills

• Experience with monitoring and observability tools

Nice to Have

• Experience with ML model serving (SageMaker, TorchServe, Triton)

• Knowledge of MLflow, Kubeflow, or MLOps platforms

• Experience with vector databases (Qdrant, Weaviate, Milvus)

• Familiarity with LLM infrastructure

Tech Stack
AWS • Terraform • Docker • Kubernetes • Python • MLflow • PostgreSQL • Qdrant • Prometheus • Grafana

What We Offer

• High-impact role in a small, fast-moving team

• Ownership of the full ML infrastructure stack

• Work with modern AI and ML systems

• Remote-first environment