ML/GenAI Engineer (N)

Sanmina Corporation; Región Centro; Presencial; MXN 500.000 - 700.000; Jornada completa

Descripción de la vacante

Sanmina Corporation is seeking a Software Engineer (Systems) 2 focused on building and deploying machine learning solutions. You will design and implement ML pipelines, leverage Vertex AI for orchestration, and optimize models with NVIDIA TensorRT for high-performance inference on GPUs.

You will work with large datasets, apply statistical analysis and predictive modeling, and integrate scalable ML services using NVIDIA microservices and GCP technologies.

Formación

• Proven experience applying statistical analysis and predictive modeling to solve real-world problems.
• Strong SQL skills and experience working with large, complex datasets.
• Proven experience building and deploying machine learning pipelines in a production environment.
• In-depth knowledge of machine learning, deep learning, and generative AI models.
• Creates and orchestrates complex machine learning workflows using Vertex AI Pipelines, automating steps from data validation to model deployment.
• Uses NVIDIA TensorRT to compile and optimize models for high-performance inference on specific NVIDIA GPUs, leveraging techniques such as quantization and layer fusion.

Responsabilidades

• Deploys models as scalable services, using Vertex AI Endpoints for seamless integration with GCP or NVIDIA Inference Microservices (NIM) for a flexible, container-based approach capable of running in cloud.

Conocimientos

Statistical analysis

Predictive modeling

SQL

Machine learning pipelines

Deep learning

Generative AI

Herramientas

Vertex AI Pipelines

Vertex AI Endpoints

TensorRT

NIM

Descripción del empleo

Category (For Job Seekers)

Information Technology

Job Description

Software Engineer (Systems) 2

• Proven experience applying statistical analysis and predictive modeling to solve real-world problems.
• Strong SQL skills and experience working with large, complex datasets.
• Proven experience building and deploying machine learning pipelines in a production

• In-depth knowledge of machine learning, deep learning, and generative AI models.
• Creates and orchestrates complex machine learning workflows using Vertex AI Pipelines, automating steps

from data validation to model deployment. 11

Uses NVIDIA TensorRT to compile and optimize models for high-performance inference on specific NVIDIA GPUs,

leveraging techniques such as quantization and layer fusion. 34

• Deploys models as scalable services, using Vertex AI Endpoints for seamless integration with GCP or NVIDIA
• NIM (NVIDIA Inference Microservices) for a flexible, container-based approach capable of running in cloud