Jobs in Zaragoza, Spain

Remote B2B Contract Europe (PL / ES / PT / CZ / CY)

We are hiring a senior MLOps / DevOps / SRE hybrid who can build an entire AI platform infrastructure end-to-end. This is not a research role and not a standard ML Engineer role. If you havent designed production-grade MLOps infrastructure havent built CI / CD for ML or havent deployed ML workloads on Kubernetes at scale this role is not a fit.

You will design build and own the AWS-based infrastructure Kubernetes platform CI / CD pipelines and observability stack that supports our AI models (Agentic AI NLU ASR Voice Biometrics TTS). You will be the technical owner of MLOps infrastructure decisions patterns and standards.

• Design and build AWS-based AI / ML infrastructure using Terraform (required).
• Define standards for security automation cost efficiency and governance.
• Architect infrastructure for ML workloads GPU / accelerators scaling and high availability.

• Architect build and operate production Kubernetes clusters.
• Containerize and productize ML models (Docker Helm).
• Deploy latency-sensitive and high-throughput models (ASR / TTS / NLU / Agentic AI).
• Ensure GPU and accelerator nodes are properly integrated and optimized.

• Build automated training validation and deployment pipelines (GitLab / Jenkins).
• Implement canary blue-green and automated rollback strategies.
• Integrate MLOps lifecycle tools (MLflow Kubeflow SageMaker Model Registry etc.).

• Implement full observability (Prometheus Grafana).
• Own uptime performance and reliability for ML production services.
• Establish monitoring for latency drift model health and infrastructure health.

• Work closely with ML engineers researchers and data scientists.
• Translate experimental models into production-ready deployments.
• Define best practices for MLOps across the company.

• 5 years in a Senior DevOps SRE or MLOps Engineering role supporting production environments.
• Strong experience designing building and maintaining Kubernetes clusters in production.
• Hands-on expertise with Terraform (or similar IaC tools) to manage cloud infrastructure.
• Solid programming skills in Python or Go for building automation tooling and ML workflows.
• Proven experience creating and maintaining CI / CD pipelines (GitLab or Jenkins).
• Practical experience deploying and supporting ML models in production (e.g. ASR TTS NLU LLM / Agentic AI).
• Familiarity with ML workflow orchestration tools such as Kubeflow Apache Airflow or similar.
• Experience with experiment tracking and model registry tools (e.g. MLflow SageMaker Model Registry ).
• Exposure to deploying models on GPU or specialized hardware (e.g. Inferentia Trainium ).
• Solid understanding of cloud infrastructure on AWS including networking scaling storage and security best practices.
• Experience with deployment tooling (Docker Helm) and observability stacks (Prometheus Grafana).

• You enjoy building platforms from the ground up and owning technical decisions.
• Youre comfortable collaborating with ML engineers researchers and software teams to turn research into stable production systems.
• You like solving performance automation and reliability challenges in distributed systems.
• You bring a structured pragmatic and scalable approach to infrastructure design.
• Energetic and proactive individual with a natural drive to take initiative and move things forward.
• Enjoys working closely with people - researchers ML engineers cloud architects product teams.
• Comfortable sharing ideas openly challenging assumptions and contributing to technical discussions.
• Collaborative mindset : you like to build together not work in isolation.
• Strong ownership mentality - you enjoy taking responsibility for systems end-to-end.
• Curious hands-on and motivated by solving complex technical challenges.
• Clear communicator who can translate technical work into practical recommendations.
• Thrives in a fast-paced environment where you can experiment improve and shape how things are done.

• Competitive fixed compensation based on experience and expertise.
• Work on cutting-edge AI systems used globall.
• Dynamic multi-disciplinary teams engaged in digital transformation.
• Remote-first work model
• Long-term B2B contract
• 20 days paid time off
• Apple gear
• Training & development budget

We are dedicated to creating and sustaining an inclusive respectful workplace for all -regardless of gender ethnicity or background. We actively encourage applicants from all identities and experience levels to apply and bring your authentic self to our fast-paced supportive team.

Apache Hive,S3,Redshift,Spark,AWS,Solr,NoSQL,Data Warehouse,Internet Of Things,Kafka,DynamoDB,ZooKeeper

Employment Type: Full Time

Experience: years

Vacancy: 1