DevOps & Cloud Infrastructure Engineer

DevOps & Cloud Infrastructure Engineer | Contract (40 hrs/week) | Fully Remote Turing is a leading AI company working with top AI labs and enterprises to advance frontier AI systems. We are seeking a hands-on DevOps and Cloud Infrastructure Engineer to build and operate the infrastructure behind Lazarus — a large-scale platform for PII detection, redaction, and human review. This is a 1-month contract (adjustable) requiring 40 hours/week with 6 hours/day overlap with PST.

What You'll Do Design, provision, and operate GCP infrastructure for PII detection and redaction pipelines. Build and manage workloads across Cloud Run, Cloud Run Jobs, Compute Engine, GKE, and GPU-backed infrastructure. Design scalable batch-processing systems capable of handling hundreds of thousands of files. Implement worker parallelism, queues, retries, checkpointing, idempotency, timeouts, and failure recovery.

Manage data movement across Google Cloud Storage, Amazon S3, VMs, containers, and external storage systems. Secure sensitive datasets using IAM, service accounts, Secret Manager, private networking, controlled egress, IAP, encryption, and audit logging. Deploy and operate containerized Python and ML workloads using Docker. Support PII and ML services such as Google Sensitive Data Protection, Presidio, OCR/vision systems, NER models, and LLM-based validation pipelines.

Provision and manage GPU infrastructure including drivers, CUDA, quotas, autoscaling, and model-serving environments. Support model-serving stacks such as vLLM, Hugging Face Transformers, and Triton. Build and maintain CI/CD pipelines for Cloud Run, VMs, containers, and related services. Establish observability through centralized logging, metrics, alerting, job tracking, and infrastructure dashboards.

Optimize throughput and cost through infrastructure selection, concurrency tuning, autoscaling, and API rate-limit management. Develop backup, recovery, migration, and disaster-recovery processes for large datasets and cloud resources. Troubleshoot production issues involving networking, storage, IAM, containers, APIs, compute, and ML infrastructure. What We're Looking For 5+ years of experience in DevOps, cloud infrastructure, platform engineering, or a related field.

Strong hands-on GCP experience including Cloud Run, Compute Engine, GKE, Cloud Storage, IAM, Secret Manager, VPC, Identity-Aware Proxy, Artifact Registry, and Cloud Logging/Monitoring. Working experience with AWS services, particularly Amazon S3 and cross-cloud data movement. Strong Linux administration and shell-scripting skills. Proficient Python skills for infrastructure automation, operational tooling, and data-processing workflows.

Strong Docker and containerization experience. Experience designing and operating large-scale batch or data-processing pipelines. Solid understanding of queues, worker parallelism, retries, checkpoints, idempotency, and failure recovery. Experience securely processing and transferring sensitive or regulated data. Experience with CI/CD tools and production deployment workflows. Exposure to ML infrastructure, GPU workloads, OCR, NLP, LLM serving, or model inference systems.

Strong problem-solving skills with the ability to independently investigate and resolve production issues. Perks of Freelancing With Turing Fully remote work environment. Opportunity to contribute to cutting-edge AI projects with leading LLM companies.