20 publicaciones de empleo destacadas de ml engineer en cuauhtémoc cdmx (¡Están contratando!)

Senior Platform Engineer
DXC Technology —Ciudad de México, CDMX
- Oracle
- JavaScript
- Presencial
Senior Software Engineer (Fullstack) - Scribd Core
Scribd, Inc. —Ciudad de México, CDMX
- Tiempo completo
- CAD
- JavaScript
- Presencial
- Seguro dental
- Vacaciones adicionales o permisos con goce de sueldo
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Senior Software Engineer, Privacy
Lyft —Ciudad de México, CDMX
- Inglés
- Investigación
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Senior Software Development Engineer
Servicios Comerciales Amazon Mexico S. de R.L. de C.V. - D44 —Ciudad de México, CDMX
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Senior Data Engineer
NielsenIQ —Ciudad de México, CDMX
- $55,000 a $70,000 por mes
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- Trabajo híbrido
- Azure
- DevOps
- Inglés
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AI Engineer
DXC Technology —Ciudad de México, CDMX
- Oracle
- Administración de personal
- Salesforce
Platform Engineer
Alcor —Ciudad de México, CDMX
- DevOps
- SQL
- Python
Postulación rápida
Data Engineer
Fresh Consulting —Ciudad de México, CDMX
- Azure
- Inglés
- SQL
Machine Learning Platform Engineer
Salesforce —Ciudad de México, CDMX
- Tiempo completo
- Administración de personal
- Salesforce
- Experiencia en bases de datos
Senior Python Engineer
Delinea —Ciudad de México, CDMX
- Tiempo completo
- Trabajo híbrido
- Azure
- Administración de personal
- Informática
- Seguro de vida
Site Reliability Engineer
Levi Strauss & Co. —Centro (Área 1), CDMX
- Tiempo completo
- Azure
- Administración de personal
- Informática
Postulación rápida
Full Stack Developer/AI Engineer
WPP —Ciudad de México, CDMX
- Azure
- Inglés
- Python
Senior Software Engineer, Iris AI
Delinea —Ciudad de México, CDMX
- Tiempo completo
- Azure
- Informática
- Licenciatura
- Seguro de vida
Senior Engineer, DevOps Engineering
Bain & Co. —Ciudad de México, CDMX
- Tiempo completo
- Azure
- Administración de personal
- Informática
Postulación rápida
Senior AI Application Engineer
Qualcomm —Ciudad de México, CDMX
- Doctorado
- Informática
- Java
Sr Data Engineer - Music DISCO, Music DISCO
Servicios Comerciales Amazon Mexico S. de R.L. de C.V. —Ciudad de México, CDMX
- Tiempo completo
- Java
- SQL
- JavaScript
Forward Deployed Engineer II, Generative AI, Global Service Delivery (English, Spanish)
Google —Ciudad de México, CDMX
- Administración de personal
- Doctorado
- Informática
Forward Deployed Engineer
Growth Protocol —Ciudad de México, CDMX
- Tiempo completo
- Trabajo híbrido
- Inglés
- Python
Postulación rápida
Staff Software Engineer (Backend) - Everand Core
Scribd, Inc. —Ciudad de México, CDMX
- Tiempo completo
- Home Office (Desde casa)
- CAD
- Capacitación
- Python
- Seguro dental
- Vacaciones adicionales o permisos con goce de sueldo
CONSULTOR C2 INGENIERO ML
Gentera —Ciudad de México, CDMX
- Python
- Seguro de vida

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Senior Platform Engineer

DXC Technology -
Ciudad de México, CDMX

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Información del empleo

Cualificaciones

Modelos de inteligencia artificial
Oracle
Node.js
Derecho
React
Kubernetes
.NET Core
C#
Microsoft SQL Server
.NET
Diseño de base de datos
Pandas
Docker
JavaScript
PostgreSQL
Redis
RabbitMQ
Redux
Angular
Kafka
GraphQL
RDS
Jenkins
TypeScript
Python

Descripción completa del empleo

Job Description:

Required Technical Skills

C# / .NET Core 8+ – deep understanding of the existing backend; required to assess, refactor, and migrate to modern architecture
Python – modern backend development, AI/ML integration, data pipelines, automation scripting, and rapid prototyping of replacement services; required across all three roles
JavaScript / TypeScript – full-stack capability for modern service development, API layers, and Node.js tooling
JSON – schema design, API contracts, configuration-as-code, LLM function calling specifications, structured data interchange
Markdown – documentation-as-code: ADRs, AI constitutions, specification documents, runbooks
Docker / Kubernetes (EKS) – containerised deployment and orchestration; Helm charts and CI/CD pipelines (Jenkins / GitLab)
Database engineering – SQL Server, Oracle RDS, and modern alternatives (PostgreSQL, columnar stores such as ClickHouse); stored procedures, query optimisation, and schema migration
Data modelling & analysis – designing data schemas for the replacement platform; understanding costing WBS trees, commodities, elements, and financial factors; data quality frameworks and analytical pipelines
GitHub Copilot and Claude Code – AI-first development as the default working mode, not an optional add-on
LLM integration – using AI models to replace rigid business logic with intelligent, adaptable solutions
API-first design – RESTful, GraphQL, and event-driven patterns for loosely-coupled architectures

Advantageous Skills

Platform migration / replatforming – strangler fig pattern, parallel running; experience shipping large-scale migrations
Event streaming – Kafka, EventBridge as replacement strategies for complex Saga chains
Redis, RabbitMQ / MassTransit – understanding current patterns to inform migration strategy
ClickHouse or modern analytics alternatives – columnar analytics for costing and reporting data
Frontend frameworks: Angular 2+, React / Redux (awareness level is sufficient)
Python data analysis libraries – pandas, SQLAlchemy for data exploration and migration validation

AI-First Cognitive Requirements

Evaluative judgment – ability to distinguish plausible AI-generated code from correct code; in high-stakes pricing logic, never self-certify money through AI alone
Specification precision – ability to articulate precise intent, edge cases, and constraints before AI generates code; quality of specification determines everything downstream
Collaborative scepticism – working productively with AI as a collaborator you direct and challenge, not a tool you wield or an oracle you trust
Constitution-building mindset – encoding failures as permanent constraints; maintaining Architecture Decision Records (ADRs) that capture why decisions were made, not just what was decided
Data-first verification – the instinct that AI is only as good as the data it works from; verifying data quality at every system boundary before trusting AI outputs

Key Responsibilities

Assess and decompose the existing 34-microservice architecture to identify simplification and replacement opportunities
Design and build next-generation backend services using modern Python / TypeScript stacks with LLM-augmented business logic
Own database architecture redesign – migrating from Oracle RDS / MSSQL to modern schemas (PostgreSQL, event stores) that are AI-queryable and analytics-ready
Build data quality frameworks and validation pipelines that ensure AI systems work from reliable, well-structured data
Replace rigid Saga / Orchestrator chains with AI-driven workflow engines and simpler event-driven patterns
Develop LLM-powered solutions to replace hard-coded costing rules, financial calculations, and allocation logic
Operate in the Intent Generate Verify Decide Document loop, owning decisions on irreversible, money-touching, or outward-facing logic
Build migration pathways (strangler fig, parallel running) to transition from legacy to modern architecture without service disruption
Performance tuning and observability using Grafana, Kibana, and the ELK stack

Knowledge Transfer & Key-Person Risk Mitigation

This role is responsible for reducing its own bus factor. Concrete expectations:

Pair regularly with the existing DB specialist to transfer backend architecture and data modelling knowledge; document all schema decisions in Markdown-based ADRs
Run fortnightly architecture clinics with the wider team covering Onion Architecture, DDD patterns, and database design for the new platform
Maintain living runbooks so that every critical backend process can be operated or debugged by at least one other team member within 60 days of joining
Contribute to CLAUDE.md-style AI constitutions encoding pricing logic constraints and data quality rules, ensuring institutional knowledge lives in the system, not just in heads
Cross-train at least one frontend developer on backend API design and Python data pipelines within the first 6 months

At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We’re committed to fostering an inclusive environment where everyone can thrive.

Recruitment fraud is a scheme in which fictitious job opportunities are offered to job seekers typically through online services, such as false websites, or through unsolicited emails claiming to be from the company. These emails may request recipients to provide personal information or to make payments as part of their illegitimate recruiting process. DXC does not make offers of employment via social media networks and DXC never asks for any money or payments from applicants at any point in the recruitment process, nor ask a job seeker to purchase IT or other equipment on our behalf. More information on employment scams is available here.

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ml engineer empleos en cuauhtémoc cdmx

Senior Platform Engineer

Senior Software Engineer (Fullstack) - Scribd Core

Senior Software Engineer, Privacy

Senior Software Development Engineer

Senior Data Engineer

AI Engineer

Platform Engineer

Data Engineer

Machine Learning Platform Engineer

Senior Python Engineer

Site Reliability Engineer

Full Stack Developer/AI Engineer

Senior Software Engineer, Iris AI

Senior Engineer, DevOps Engineering

Senior AI Application Engineer

Sr Data Engineer - Music DISCO, Music DISCO

Forward Deployed Engineer II, Generative AI, Global Service Delivery (English, Spanish)

Forward Deployed Engineer

Staff Software Engineer (Backend) - Everand Core

CONSULTOR C2 INGENIERO ML

Quiero recibir la alerta de empleo más reciente para ml engineer en cuauhtémoc cdmx

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Required Technical Skills

C# / .NET Core 8+ – deep understanding of the existing backend; required to assess, refactor, and migrate to modern architecture

Advantageous Skills

Platform migration / replatforming – strangler fig pattern, parallel running; experience shipping large-scale migrations

AI-First Cognitive Requirements

Evaluative judgment – ability to distinguish plausible AI-generated code from correct code; in high-stakes pricing logic, never self-certify money through AI alone

Key Responsibilities

Assess and decompose the existing 34-microservice architecture to identify simplification and replacement opportunities

Knowledge Transfer & Key-Person Risk Mitigation

This role is responsible for reducing its own bus factor. Concrete expectations:

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