AI/ML Platform Engineer - Production-Grade MLOps

World Wide Technology; Maryland Heights (MO); On-site; USD 104,000 - 130,000; Full time

Benefits offered by this job

Health and Wellbeing

401k Plan with Company Matching

Paid Time Off

Onsite Health Centers

Tuition Reimbursement

Voluntary Legal

Pet Insurance

Employee Discount Program

Flexible Spending Accounts

Job summary

World Wide Technology (WWT) seeks a Solutions Consulting & Engineering professional to develop, productionize, and deploy AI/ML solutions within client environments, spanning cloud and on‑prem. You will design ML pipelines, build scalable infrastructure, and collaborate in cross-functional teams.

Ideal candidates have hands-on Kubernetes, cloud, and MLOps experience, plus strong Python/SQL skills and excellent communication.

Qualifications

• Experience deploying AI and ML systems in production.
• Hands-on Kubernetes production experience.
• Working depth in at least one major cloud (AWS, Azure, GCP).
• Understanding of production behavior of LLMs and models.
• Experience with AI coding agents and guardrails.
• Infrastructure as code and CI/CD practices.
• MLOps tooling and platforms (Databricks, SageMaker, Azure ML, Vertex AI, etc.).
• Observability for ML/LLM workloads (Prometheus, Grafana, OpenTelemetry).
• Proficiency in Python, SQL, and shell scripting.
• Familiarity with cloud data platforms (Snowflake, Databricks, Microsoft Fabric).
• Clear written and spoken communication with engineers and clients.

Responsibilities

• Develop, productionize, and deploy cutting-edge AI & ML solutions inside client environments; both cloud and on‑prem.
• Build and run infrastructure models on Kubernetes clusters, GPU management, model serving, and CI/CD pipelines.
• Design and build ML pipelines: feature extraction, training, validation, and deployment at scale.
• Deploy solutions with infra as code, observability, guardrails, and cost controls.
• Collaborate in cross‑functional agile teams and mentor engineers in software delivery and AI engineering.
• Document reusable patterns, reference architectures, and accelerators from engagements.
• Support pre‑sales scoping and internal R&D.
• Stay current on AI developments and provide pragmatic guidance to teammates and clients.

Skills

AI deployment

Kubernetes

Cloud platforms

LLM in production

AI agents

IaC & CI/CD

MLOps tools

Observability

Python

SQL

Shell scripting

ML lifecycle

Cloud data platforms

Communication

Tools

Terraform

Pulumi

Ansible

GitHub Actions

GitLab CI

Azure DevOps

Databricks

SageMaker

Vertex AI

Prometheus

Grafana

OpenTelemetry

LangFuse

LangSmith

Arize

Job description

World Wide Technology (WWT) seeks a Solutions Consulting & Engineering professional to develop, productionize, and deploy AI/ML solutions within client environments, spanning cloud and on‑prem. You will design ML pipelines, build scalable infrastructure, and collaborate in cross-functional teams.

Ideal candidates have hands-on Kubernetes, cloud, and MLOps experience, plus strong Python/SQL skills and excellent communication.