17 publicaciones de empleo destacadas de python developer en cuajimalpa, dif (¡Están contratando!)

Customer Engineer, Public Sector
Google —Ciudad de México, CDMX
- Inglés
- Licenciatura
- Sin título de educación superior
21h
Software Engineer, AI Agent Platform
QAD, Inc. —Ciudad de México, CDMX
- Tiempo completo
- Home Office (Desde casa)
- Experiencia en manufactura
- Liderazgo
- Python
Postulación rápida
10h
Software Engineer, AI Agent Platform
QAD —Ciudad de México, CDMX
- Tiempo completo
- Experiencia en manufactura
- Liderazgo
- Python
6h
Lead Software Engineer
Mastercard —Ciudad de México, CDMX
- Tiempo completo
- Azure
- Informática
- Java
2h
Database Architect
Luxoft —Ciudad de México, CDMX
- Oracle
- Inglés
- Experiencia en bases de datos
17h
Senior Software Engineer
Mastercard —Ciudad de México, CDMX
- Tiempo completo
- Azure
- Java
- JavaScript
9h
Pre-Sales Solutions Architect
MongoDB —Ciudad de México, CDMX
- Azure
- Experiencia en ventas
- DevOps
- Permiso de maternidad y paternidad
Senior Software Engineer
Umba —Ciudad de México, CDMX
- DevOps
- Java
- JavaScript
Postulación rápida
Senior Software Engineer
Zendesk —Ciudad de México, CDMX
- Tiempo completo
- Azure
- Administración de personal
- Informática
Senior Software Engineer
BlackLine —Ciudad de México, CDMX
- Informática
- Java
- Maestría
12d
Senior Software Engineer
EarnIn —Ciudad de México, CDMX
- Home Office (Desde casa)
- Administración de personal
- Liderazgo
- Python
Postulación rápida
Senior Payments Engineer — Acquiring & Payment Processing
Sezzle —Ciudad de México, CDMX
- Tiempo completo
- Home Office (Desde casa)
- Informática
- DevOps
- SQL
1d
Senior Platform Engineer
Kiwi Financial Inc —Ciudad de México, CDMX
- Tiempo completo
- Home Office (Desde casa)
- DevOps
- Inglés
- Linux
Senior Engineering Manager Payments
Belvo —Ciudad de México, CDMX
- Tiempo completo
- Home Office (Desde casa)
- Administración de personal
- Inglés
- JavaScript
- Vacaciones adicionales o permisos con goce de sueldo
- Horarios flexibles
8d
Senior Java Developer
CMAS Adquirente, S. de R.L. de C.V. —Cuajimalpa, CDMX
- Oracle
- Informática
- Java
Postulación rápida
1d
Data Scientist / Analytics Analyst
Ford de México —Naucalpan, Méx.
- Tiempo completo
- Microsoft Excel
- Informática
- Experiencia en ventas
2h
Data Scientist / Analytics Analyst
Ford Motor Company —Naucalpan, Méx.
- Microsoft Excel
- Informática
- Experiencia en ventas
4h

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Software Engineer, AI Agent Platform
QAD, Inc. —Ciudad de México, CDMX
Experience with the Strands agent SDK or a comparable agentic framework. This engineer joins the core platform team with three main areas of focus: building new…
Postulación rápida
10h
Software Engineer, AI Agent Platform
QAD —Ciudad de México, CDMX
Experience with the Strands agent SDK or a comparable agentic framework. This engineer joins the core platform team with three main areas of focus: building new…
6h

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Customer Engineer, Public Sector

Google -
Ciudad de México, CDMX

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Información del empleo

Hace 21 horas

Cualificaciones

Modelos de inteligencia artificial
TensorFlow
Derecho
Kubernetes
PyTorch
Inglés
Google Cloud Platform
Docker
Licenciatura
Desarrollo de software
Seguridad
Python

Descripción completa del empleo

Please submit your resume in English - we can only consider applications submitted in this language.

Only applications of candidates with Mexican citizenship will be evaluated for this role in compliance with the provisions of Article 7 of the Federal Labor Law.

Minimum qualifications:

Bachelor's degree or equivalent practical experience.
10 years of experience in AI/ML development, AI infrastructure engineering, or software development.
5 years of experience with containerization (e.g., Docker) and orchestration (e.g., Kubernetes).
5 years of experience with Python and with libraries like PyTorch, TensorFlow, or Hugging Face Transformers.
Ability to travel up to 25% of the time as needed.
Must possess an active Top Secret/SCI security clearance with current polygraph.

Preferred qualifications:

5 years of experience in AI/ML research or software development.
Experience with LLM deployment frameworks such as vLLM, NVIDIA Triton, or Ollama and agent development.
Knowledge of open worldwide application security project (OWASP) for LLMs or similar security frameworks.
Familiarity with cloud-native AI services (e.g., cloud computing platform, Google Vertex AI).
Track record of deploying AI models on air-gapped or on-premises high-performance computing (HPC) systems.

About the job

When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

Architect and manage Large Language Model (LLM) deployments across on-premises (NVIDIA/AMD) and cloud (cloud computing platform, Google Cloud platform (GCP) environments. Audit multi-agent orchestration, agent construction, and vector databases to map data flows and enforce privilege boundaries.
Use Docker and Kubernetes to orchestrate scalable inference and training environments, optimizing Graphics Processing Unit (GPU) utilization and resource isolation.
Protect model weights, secure data ingestion, and harden inference endpoints across the Machine Learning operations (MLOps) lifecycle. Investigate and mitigate AI-specific threats (e.g., prompt injection, jailbreaking, data poisoning). Map testing findings to MITRE ATLAS, OWASP for LLMs, and STRIDE models.
Bridge local high-compute clusters and cloud AI services while maintaining a consistent security posture.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

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