MLOps Engineer

World Wide Technology; Maryland Heights (MO); Sur place; USD 104 000 - 130 000; Plein temps

Avantages offerts par ce poste

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

Résumé du poste

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.

Responsabilités

• 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.

Connaissances

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

Outils

Terraform

Pulumi

Ansible

GitHub Actions

GitLab CI

Azure DevOps

Databricks

SageMaker

Vertex AI

Prometheus

Grafana

OpenTelemetry

LangFuse

LangSmith

Arize

Description du poste

Why WWT?

World Wide Technology (WWT) strives to make a new world happen. WWT's work benefits clients and partners as much as it does its people and community across the globe.

Founded in 1990, WWT brings together strategy, deep technical expertise and world-class partnerships to help public and private sector organizations design, build and scale intelligent AI, digital, cybersecurity, cloud and infrastructure solutions. Through its Advanced Technology Center (ATC)—a collaborative ecosystem featuring state-of-the-art hardware and software—WWT enables clients and partners to conceptualize, test and validate innovative technology and then deploy solutions at scale using its global integration and distributions capabilities.

With more than 14,000 team members and over 60 locations globally, WWT's culture—grounded in core values and leadership philosophies—has been recognized by Fortune® and Great Place to Work for its commitment to innovation, trust and creating a great place to work for all. WWT provides products and services to large enterprise, global service provider and public sector clients in up to 130 countries across six continents. Softchoice, a World Wide Technology company, supports commercial and SMB markets in the U.S. and Canada.

What is the Solutions Consulting & Engineering (SC&E) Team and why join?

Solutions Consulting & Engineering is an organization that is Customer Focused and Solutions Led. We deliver end-to-end (E2E) and emerging solutions to drive customer satisfaction, increase profitability and growth. Our success is enabled by our world-class management consulting, delivery excellence and engineering brilliance. We embody the OneWWT mindset by bringing the right talent at the right time from anywhere within WWT to solve our customer's problems. Our goal is to bring together business acumen with full-stack technical know-how to develop innovative solutions for our clients' most complex challenges.

RESPONSIBILITIES

• Develop, productionize, and deploy cutting-edge AI & ML solutions inside client environments; both cloud and on-prem
• Build and operationalize the infrastructure models run on: Kubernetes clusters, GPU management, model serving, AI gateways, and the CI/CD pipelines that promote models between environments.
• Design and build ML pipelines: feature extraction and transformation, training and retraining jobs, model registry, validation gates, and deployment at scale.
• Deploy solutions with enterprise rigor; infrastructure as code, observability, guardrails, cost controls. Proactively identify issues with production readiness, security, or architecture reviews, and develop solutions.
• Work in cross-functional agile teams with WWT data scientists, data engineers, engagement managers, etc. from scoping through delivery. Coach teammates on software delivery excellence (version control, automated testing, release management, and environment hygiene) and AI-native engineering (coding agent use, harness engineering, MCP servers, spec-driven development).
• Bring what you learn on engagements back to the practice as reusable patterns, reference architectures, and accelerators. Support pre‑sales scoping and internal R&D.
• Stay current on new developments in AI (models, techniques, tooling and platforms) and provide pragmatic advice to teammates and clients.

QUALIFICATIONS

• Experience deploying AI and ML systems in production. Experience working on project-based or consulting teams that deliver into client environment is preferred.
• Hands‑on Kubernetes experience in production: Helm, ingress, persistent storage, autoscaling, and GPU scheduling.
• Working depth in at least one major cloud (AWS, Azure, GCP): provisioning, IAM, networking, autoscaling, and its managed AI/ML services.
• Understanding of how LLM systems behave in production: model serving and quantization, GPU memory sizing, vector databases, RAG components, and gateway and guardrail layers.
• Regular use of AI coding agents in your own production work, and experience shaping how they behave: writing tool and MCP server definitions, maintaining repository context files, building eval suites, and setting guardrails.
• Infrastructure as code and CI/CD: Terraform or Pulumi, Ansible, GitHub Actions or GitLab CI or Azure DevOps, container builds, trunk‑based development, and test‑driven development.
• Experience with MLOps tooling and platforms: MLflow, Kubeflow, model registries, feature stores, and at least one of Databricks, SageMaker, Azure ML, Vertex AI, Domino, or Dataiku.
• Observability for ML and LLM workloads: Prometheus and Grafana, OpenTelemetry, LLM tracing tools (LangFuse, LangSmith, Arize, or similar), drift monitoring, and cost tracking.
• Experience with common data science languages; Python, SQL, and shell scripting.
• Knowledge of the ML lifecycle (data wrangling, model selection, training, validation, deployment, retraining) and experience working day to day with data scientists.
• Familiarity with cloud data platforms such as Snowflake, Databricks, or Microsoft Fabric.
• Clear written and spoken communication with teammates, client engineers, and executives. Comfortable presenting architecture decisions and tradeoffs, and experience mentoring other engineers.

Preferred

• On‑prem or hybrid infrastructure experience: GPU servers, the NVIDIA software stack (drivers, CUDA, NIM, Triton, AI Enterprise), and the storage and networking that training and inference workloads demand.
• Experience influencing and building mindshare convincingly with any audience. Confident and experienced in public speaking.
• Ability to communicate complex ideas in a concise way. Fluent with popular diagraming and presentation software.

A reasonable estimate of the current base pay range for this position is $104,000 to $130,000 annually. Actual salary will be based on a variety of factors, including shift, location, experience, skill set, performance, licensure and certification, and business needs. The range for this position in other geographic locations may differ. Certain positions may also be eligible for variable incentive compensation, such as bonuses or commissions, that are not included in the base pay.

Benefits

• Health and Wellbeing: Health (Medical & Prescription), Dental, and Vision Care, Onsite Health Centers (MO & IL), Employee Assistance Program, Wellness program
• Financial Benefits: Competitive Pay, Profit Sharing, 401k Plan with Company Matching, Life and Disability Insurance, Flexible Spending Accounts, Tuition Reimbursement
• Paid Time Off: PTO & Holidays, Parental Leave, Medical Leave, Military Leave, Bereavement, Day of Caring
• Additional Perks: Family Planning Benefits, Nursing Mothers Benefits, Voluntary Legal, Voluntary Supplemental Accident/Illness/Hospital, Voluntary ID Theft, Pet Insurance, Employee Discount Program

Note: This is not an all-encompassing list and should not be used as a complete description of the plan’s benefits. For more information, see our US benefits website at wwt.com/us-benefits.

We strive to create an environment where all employees are empowered to succeed based on their skills, performance, and dedication. Our goal is to cultivate a culture of belonging that encourages innovation, collaboration, and respect for all team members, ensuring that WWT remains a great place to work for all!

World Wide Technology is an Equal Opportunity Employer.