Devops Engineer with Strong MLOPS

Devops Engineer with MLOPS

Location : Remote (TX)

FULL TIME/W2 (NO C2C)

Need 10 Plus Years Profile

• JOB DESCRIPTION
• One of our largest Telecom customers is seeking a skilled DevOps Engineer to join their Data Platform team within the Chief Data Office.
• This Engineer will play a key role in building, operating, and scaling a production-grade AI inferencing platform that supports high-throughput, low-latency large language model (LLM) workloads.
• The position combines software engineering, platform engineering, and reliability engineering responsibilities, with a focus on developing Python-based services, automating model deployments, and optimizing model serving performance using vLLM, Kubernetes, KServe, and Knative.
• The engineer will be responsible for containerization with Docker and Podman, maintaining and tuning PostgreSQL data models, troubleshooting production issues, and driving platform reliability through observability and automation.
• Working closely with ML engineers and platform architects, this individual will help scale mission-critical AI services, support new model rollouts, and continuously improve the infrastructure that powers enterprise AI applications.

REQUIRED SKILLS AND EXPERIENCE

-Strong hands-on python coding & development experience as well as experience working with FastAPI

-Expertise with Docker & Kubernetes, including deployments, services, autoscaling, and

troubleshooting workloads in production.

-Practical experience with Postgres, including query optimization and schema design.

-Cloud platform experience, such as Azure/AKS, AWS/EKS, or GCP/GKE.

-Strong debugging skills across the stack — from application code to infrastructure

NICE TO HAVE SKILLS AND EXPERIENCE

-Direct experience with vLLM or LLM inferencing

-Experience with GPU-aware scheduling and resource management in Kubernetes.

-Familiarity with LLM-specific optimizations: speculative decoding, quantization (FP8/INT8), KV cache

management, and continuous batching.

-Experience with API gateways or LLM routing layers, such as LiteLLM or similar.

-Background in SRE practices: SLOs/SLAs, incident response, and on-call tooling.

-Experience with Helm, ArgoCD, or other GitOps deployment tooling.

-Familiarity with observability stacks, including Prometheus, Grafana, and OpenTelemetry