GenAI Platform Engineer: Build & Scale AI Tools

HP; Tlaquepaque; Presencial; MXN 2.528.000 - 3.969.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Dental insurance

Vision insurance

Disability insurance

Employee assistance program

Flexible spending account

Life insurance

Parental leave (4–12 weeks)

Holidays

Descripción de la vacante

HP is seeking an AI/ML Platform Engineer to join a builder-first, highly collaborative team. The role focuses on hands-on coding, platform tooling, and enabling internal teams with scalable AI/ML infrastructure.

You will work across Terraform, AWS, Azure, and Kubernetes, with emphasis on deploying models and reducing friction for platform adopters. Strong software engineering and ML expertise are required.

Formación

• <1> Four-year or graduate degree in CS/Math/Data Science or related field.</1>
• <2> 7–10 years of work experience in programming, ML, algorithms, or related field.</2>

Responsabilidades

• Build internal platform tools, self-service portals, and CI/CD tooling.
• Develop and maintain backend APIs (Python/FastAPI).
• Assist in model deployment, inference patterns, and scaling (SageMaker, Bedrock, Azure ML).
• Collaborate with teams, review designs, and guide architecture decisions.
• Document platforms, onboarding guides, and best practices.

Conocimientos

Python

Machine Learning

Deep Learning

C++

Java

TensorFlow

PyTorch

Scikit-learn

AWS

Microsoft Azure

Natural Language Processing

Algorithms

Data Science

Software Engineering

Educación

Four-year or Graduate Degree in Computer Science, Statistics, Mathematics, Data Science

Herramientas

SageMaker

Bedrock

Azure Machine Learning

Kubernetes

Terraform

Descripción del empleo

HP is seeking an AI/ML Platform Engineer to join a builder-first, highly collaborative team. The role focuses on hands-on coding, platform tooling, and enabling internal teams with scalable AI/ML infrastructure.

You will work across Terraform, AWS, Azure, and Kubernetes, with emphasis on deploying models and reducing friction for platform adopters. Strong software engineering and ML expertise are required.