Pre-Silicon Fpga Platform Engineer — Emulation & Rtl

Intel; Región Centro; Presencial; MXN 700.000 - 900.000; Jornada completa

Descripción de la vacante

Intel is seeking an AI/ML Platform Engineer to join a dynamic centralized platform team focused on Generative AI and large language models. You will shift fluidly between writing code, debugging infrastructure, and guiding architectural decisions, with roughly half the time on hands-on development and half on collaboration and enablement.

You will build internal platform tools and services (Python/FastAPI), manage CI/CD tooling, Terraform for AWS and Azure, and support model deployment across

Formación

• Four-year or graduate degree in CS/Math/Data Science or related field.
• Ability to translate ambiguous requirements into practical plans.
• Experience building and deploying AI/ML platform tools and services.

Responsabilidades

• Build internal platform tools and services with Python/FastAPI.
• Manage MCP/gateway integrations and AI-enabled automations.
• Write and maintain Terraform for cloud resources (AWS/Azure).
• Collaborate in standups, design reviews, and onboarding new teams.
• Support model deployment across SageMaker, Bedrock, Azure ML, and Kubernetes.
• Document platform improvements and onboarding guides.

Conocimientos

Collaboration

Architectural thinking

Troubleshooting

Code writing

Educación

Bachelor's or higher in CS/Math/Data Science

Herramientas

Terraform

AWS

Azure

Kubernetes

SageMaker

Bedrock

FastAPI

Descripción del empleo

AI/ML Platform Engineer

Description - We are a dynamic centralized platform team dedicated to harnessing cutting‑edge AI/ML technology, particularly in the realm of Generative AI and large language models, to empower HP and drive innovation. Collaborating closely with various business units, we provide strategic advice, prototype solutions, and develop and manage software applications tailored for internal use. Days split roughly evenly between hands‑on building and collaboration/enablement, driven by a mix of roadmap work and incoming requests. Expect to shift context often.

Building (largest share of the day)

• Internal platform tools and services: self‑service portals/workbenches, backend APIs (Python/FastAPI), automations and CI/CD tooling
• MCP/gateway integrations and AI‑enabled automations and flows
• Focus is always on reducing friction for teams adopting the platform

Cloud infrastructure & troubleshooting (weekly)

• Writing and maintaining Terraform; provisioning and configuring platform resources across AWS and Azure
• Diagnosing deployment, networking, endpoint, and configuration issues
• Enough depth to reason about deployments and partner with security/networking specialists

Collaboration & enablement (about half the day)

• Standups, syncs, and planning/project meetings
• Design and architecture reviews; regular PR and code review
• Onboarding new teams; translating ambiguous requirements into practical plans and challenging weak designs

Model deployment support (recurring)

• Helping teams productionize models‑hosting options, inference patterns, scaling, cost, and operational readiness across SageMaker, Bedrock, Azure ML/AI Foundry, and Kubernetes

Docs & platform improvement (ongoing)

• Documentation, onboarding guides, and reference examples
• Ad‑hoc process and platform improvements-spotting and fixing rough edges proactively

In short: a builder‑first role with a strong collaborative and enablement component‑someone who moves fluidly between writing code, reviewing work, troubleshooting infrastructure, and guiding architectural decisions.Education & Experience Recommended

• Four‑year or Graduate Degree in Computer Science, Statistics, Mathematics, Data Science, or any other related discipline or commensurate work experience or demonstrated competence.