20 publicaciones de empleo destacadas en ai data platform engineer (mlops) (¡Están contratando!)

Data Engineer
ESML SD Iberia Holding S A U —Los Montoyos, Alicante provincia
- Jornada completa
- Azure
- DevOps
- Inglés
Solicitud rápida
Senior AI Engineer
Bsport —Barcelona, Barcelona provincia
- Trabajo híbrido
- Máster
- AWS
- Machine learning
- Teletrabajo opcional
AI Engineer / Backend Developer
Mindsight Ventures —Barcelona, Barcelona provincia
- Jornada completa
- Trabajo híbrido
- Azure
- DevOps
- Investigación
Senior Machine Learning Engineer – Generative AI / LLMs
Accenture —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Español
- Informática
- DevOps
Senior AI Backend Engineer
SIX Group AG —Madrid, Madrid provincia
- Teletrabajo
- Azure
- Informática
- DevOps
Applied AI Engineer & AI Enablement
ailylabs —Barcelona, Barcelona provincia
- Jornada completa
- Azure
- Máster
- SQL
Solicitud rápida
4d
Senior AI Platform Engineer (Domino)
EPAM Systems, Inc. —Barcelona, Barcelona provincia
- Informática
- DevOps
- Oficina
- Vacaciones pagadas
- Programa de recomendación
12d
Senior Applied AI Engineer – Developer Productivity & SDLC
Keysight Technologies, Inc. —Barcelona, Barcelona provincia
- Media jornada
- Informática
- Máster
- Grado
AI Engineer
Unit4 —Granada, Granada provincia
- Jornada completa
- Trabajo híbrido
- Azure
- Sistemas ERP
- Inglés
- Vacaciones pagadas
Solicitud rápida
2d
Senior Machine Learning Engineer – LLMs & Agentic AI
Keysight Technologies, Inc. —Barcelona, Barcelona provincia
- Media jornada
- Azure
- Doctorado
- Informática
Principal AI Engineer - Evinova
AstraZeneca —Barcelona, Barcelona provincia
- Jornada completa
- Microsoft Excel
- Informática
- Oficina
6d
Senior MLOps Engineer
NN Group —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Azure
- Inglés
- AWS
- Parking gratuito
- Seguro de vida
6d
Senior Data Platform Engineer
SeQura —Barcelona, Barcelona provincia
- Jornada completa
- Trabajo híbrido
- Inglés
- AWS
- Grado
Solicitud rápida
GCP Senior AI Engineer
BIP - Business Integration Partners —Madrid, Madrid provincia
- Jornada completa
- Español
- Informática
- Inglés
Platform Engineer (Fintech)
Merlin Digital Partner —Barcelona, Barcelona provincia
- Trabajo híbrido
- DevOps
- AWS
- Machine learning
Solicitud rápida
6d
AI Voice Agents Engineering Lead
ISB Santander Global Technology and Operations, S.L. —Santa Bàrbara, Tarragona provincia
- Jornada completa
- Azure
- Informática
- Máster
- Abono gimnasio
- Seguro de vida
MLOps Engineer
MULTIVERSE COMPUTING —Donostia-San Sebastián, Guipúzcoa provincia
- Español
- Azure
- Informática
Solicitud rápida
AI Solutions Architect
WATA Factory —Toledo provincia
- Jornada completa
- Azure
- Sistemas ERP
- Inglés
- Teletrabajo opcional
Senior AI Engineer – Consulting & Delivery Lead
Orange Business —Madrid, Madrid provincia
- Trabajo híbrido
- Español
- Azure
- DevOps
AI Program Manager
Allianz —Barcelona, Barcelona provincia
- Jornada completa
- Trabajo híbrido
- Azure
- Máster
- AWS
- Plan de pensiones

Quiero recibir la alerta de empleo más reciente de ai data platform engineer (mlops)

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Data Engineer

ESML SD Iberia Holding S A U -
Los Montoyos, Alicante provincia

Solicitud rápida

Detalles del empleo

Jornada completa

Cualificaciones

CI/CD
Azure
Derecho
DevOps
Inglés
Máster
Kernel
AWS
Docker
Machine learning
Terraform
NLP
GitHub
Escalabilidad
Cloud
Inteligencia artificial
Jenkins
GitLab
Python

Descripción completa del empleo

We are looking for a MLOps / AIOps / LLMOps / AgentOps Engineer to join a multidisciplinary Data & AI team. The main mission of this role is to design, operate, and continuously evolve our AIOps platform, ensuring that our AI products run in a reliable, scalable, and cost‑efficient way.

This position is strongly focused on platform, infrastructure, automation, observability, and operations rather than on building ML models or AI products themselves.

You will work with modern cloud technologies (mainly AWS, with some Azure exposure) and collaborate closely with Data Scientists, Data Engineers, and Product teams to bring AI solutions into production and keep them running smoothly.

We are open to candidates with strong expertise in at least one core area (e.g. cloud, DevOps, platform engineering, or ML operations) and solid foundational knowledge in the others, with motivation to grow across the full AI operations stack.

Key Responsibilities

Design, maintain, and evolve the AIOps platform supporting:
- Traditional machine learning models in production
- LLM‑based solutions such as RAG pipelines and AI Agents
- Speech Analytics use cases (ASR, conversation analysis, NLP)
Build and operate ML and LLM pipelines with a strong focus on:
- Reliability, automation, and observability
- Model and LLM quality, performance, and drift monitoring
- Cloud cost control and optimization
Implement LLMOps / AgentOps practices, including:
- LLM evaluation and observability
- Prompt management, traceability, and specialized logging
- Agent integration, orchestration, and lifecycle management
Ensure continuous operation of AI products, including:
- Alerts, dashboards, SLOs / SLIs
- Scalability strategies and basic auto‑remediation mechanisms
Manage deployments in cloud environments (AWS / Azure) and container platforms (Docker / Kubernetes)
Collaborate closely with Data Scientists and Data Engineers to productionize robust, scalable AI solutions
Contribute to internal standards, automation, and best practices across the AI and data ecosystem

Required Skills (Must Have)

Hands‑on experience in MLOps, AIOps, or operating ML systems in production
Solid understanding of LLMOps and AgentOps concepts (RAGs, agents, evaluation, monitoring)
Experience working with AWS and/or Azure in production environments
Practical knowledge of containers and Kubernetes (Docker, basic Helm usage, etc.)
Experience with CI/CD pipelines (GitHub Actions, GitLab CI, Azure DevOps, Jenkins, or similar)
Familiarity with observability and monitoring concepts (CloudWatch, OpenTelemetry, Prometheus, etc.)
Experience managing infrastructure as code (Terraform, Bicep, CDK, or similar)
Python experience and familiarity with the ML ecosystem (e.g. scikit‑learn, PyTorch), even if not a Data Scientist
Good understanding of the ML / LLM lifecycle, from development to production and monitoring
Fluent English to work in an international environment

Nice to Have (Not Required, but Valuable)

Experience with ML/AI platforms such as SageMaker, Azure ML, MLflow, Kubeflow
Exposure to Speech Analytics technologies (ASR, diarization, conversational NLP)
Experience with cloud cost optimization / FinOps, especially for AI workloads
Experience building or operating AI agents, copilots, or conversational systems
Familiarity with LLM frameworks (LangChain, LlamaIndex, Semantic Kernel, etc.)
Experience with workflow and orchestration tools (Airflow, Argo, Step Functions, Durable Functions)

Professional Skills & Mindset

Strong focus on reliability, automation, and scalability
Ability to collaborate effectively in multidisciplinary teams
Clear communication and documentation‑oriented mindset
Platform mindset: building reusable, maintainable, and robust solutions
Proactive, analytical, and continuous‑improvement driven
Strong sense of ownership and end‑to‑end responsibility
Motivation to learn and grow across the AI operations stack

Technology Environment

Cloud: AWS, Azure
Orchestration & Containers: Kubernetes, Docker
CI/CD: GitHub Actions, GitLab CI, Azure DevOps
Observability: Prometheus, Grafana, ELK/EFK, OpenTelemetry
Infrastructure as Code: Terraform, Bicep, CloudFormation
AI / ML Tools: MLflow, Azure ML, SageMaker, LangChain, LlamaIndex, Semantic Kernel
Primary Language: Python

Solicitud rápida

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