Senior MLOps Engineer at Pumex Computing, LLC

• Job Location New York, NY
• Seniority Mid-Senior Level
• Type Full-time

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Description

Senior MLOps Engineer (Hybrid — NYC) Pumex Computing is supporting a leading global technology organization in hiring a Senior MLOps Engineer to drive the next generation of cloud-native, AI-powered platforms.

In this role, you'll design and scale the ML infrastructure that powers intelligent applications used by millions.

You’ll work at the intersection of ML Engineering, DevOps, and Cloud Platform Architecture taking machine learning models from research to secure, scalable real-world deployment.

What You’ll Do Lead design and automation of end-to-end MLOps pipelines : model training, deployment, versioning, and monitoring Build and operate production ML services on Kubernetes (GKE) Develop high-performance Python APIs using FastAPI or Flask to serve ML models and platform services Architect scalable cloud environments using Google Cloud Platform (GCP) Own CI/CD workflows (GitHub Actions) and infrastructure automation (Terraform / Helm / Crossplane) Build data ingestion and transformation pipelines supporting ML workloads (Airflow / Dagster) Implement advanced monitoring & observability (Prometheus, Grafana, Cloud Logging) Apply security best practices across cloud, data, and service layers Collaborate with Data Science & Engineering teams; mentor junior engineers What You Bring 5+ years in Cloud, DevOps, or Data Engineering roles 2+ years hands-on MLOps experience in production environments Deep Python expertise for API development, automation, and ML pipelines Experience deploying containerized services with Docker & Kubernetes Strong knowledge of GCP (BigQuery, Vertex AI, GCS, Pub/Sub preferred) CI/CD pipeline experience (GitHub Actions) Infra-as-Code (Terraform) & config-as-code (Helm / Crossplane) Data pipeline experience (Airflow or Dagster) Strong communication and problem-solving abilities Compensation & Details Location: Hybrid - New York City Full-time, long-term engagement Competitive compensation + benefits (details shared during intro call)