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Gcp Mlops Engineer | Vertex Ai & Production Ml

Grupo TECDATA Engineering
Las Rozas de Madrid, Spain
17 days ago
Apply on www.buscojobs.com.es
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source
www.buscojobs.com.es

Tech stack

Artificial Intelligence BigQuery DevOps Github Python (Programming Language) Machine Learning Xgboost Machine Learning Operations Docker

Job description

Grupo Tecdata Engineering busca un/a Machine Learning Engineer / MLOps con experiencia en GCP, Python y desarrollo de modelos para producción.Ubicación en Las Rozas (Madrid) con modalidad híbrida: 1 día presencial por semana.Se trabajará con volúmenes de datos grandes y pipelines de datos.Se valorará experiencia con Vertex AI, BigQuery, pipelines, versionado de modelos y despliegues reproducibles, así como conocimientos de DevOps (Docker, GitHub Actions) y herramientas de ML (LightGBM, #J-*****-Ljbffr

Requirements

Se valorará experiencia con Vertex AI, BigQuery, pipelines, versionado de modelos y despliegues reproducibles, así como conocimientos de DevOps (Docker, GitHub Actions) y herramientas de ML (LightGBM, #J-*****-Ljbffr

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.buscojobs.com.es
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

Moments

Explore playlists

2:17 min

Mapping the maturity roadmap for scaled devops adoption

Dominik Krichbaum Dominik Krichbaum · World Congress 2026 Europe

6:36 min

Funding open source through GitHub Accelerator and Sponsors

Stormy Peters · World Congress 2023

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · World Congress 2025

1:49 min

Building the machine learning engineering pipeline

Dora Petrella · World Congress 2023

3:18 min

Scaling global network engineering through DevOps culture

Stuart Clark · LIVE

2:08 min

Essential engineering roles in the generative AI space

Mary Grygleski Mary Grygleski · LIVE

Videos

See all
From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform thumbnail
22:57
World Congress 2026 Europe • 3 months ago

From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform

Dominik Krichbaum

Innovating Developer Tools with AI: Insights from GitHub Next thumbnail
42:38
LIVE • almost 2 years ago

Innovating Developer Tools with AI: Insights from GitHub Next

Krzystof Czieslak

Docker Compose: Rediscovered thumbnail
28:40
Europe 2026 Virtual • 3 months ago

Docker Compose: Rediscovered

Matthieu Vincent

How E.On productionizes its AI model & Implementation of Secure Generative AI. thumbnail
19:27
World Congress 2023 • about 3 years ago

How E.On productionizes its AI model & Implementation of Secure Generative AI.

Kapil Gupta

DevOps Maturity Check – a way to balance autonomy and alignment thumbnail
42:52
LIVE • almost 6 years ago

DevOps Maturity Check – a way to balance autonomy and alignment

Martin Thalmann

LLMOps-driven fine-tuning, evaluation, and inference with NVIDIA NIM & NeMo Microservices thumbnail
29:20
World Congress 2025 • about 1 year ago

LLMOps-driven fine-tuning, evaluation, and inference with NVIDIA NIM & NeMo Microservices

Anshul Jindal

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