Remuneration
Benefits bonus, private medical insurance, and life insurance
Location
Madrid, MD, Spain
Visa sponsorship
Not specified
Job summary
The Senior MLOps Engineer develops, deploys, and maintains AI and machine learning solutions in production, combining software engineering, automation, and machine learning in collaboration with data science, DevOps, and business teams. The role builds Python applications and models, manages Kubernetes deployments, designs ETL pipelines with Spark, integrates REST APIs, and automates CI/CD testing and releases. It also monitors production systems to maintain performance and reliability.
Benefits
Flexible working arrangements and teleworkPoint-based vacation systemTrainingPrivate medical insuranceLife insurancePersonal trainerWellbeing programOutdoor activitiesSports competitionsStreaming platform subscriptionBenefits bonus
Qualifications
- At least 4 years of experience developing and maintaining production applications with AI components.
- Proficiency in Python, SQL, and Kubernetes.
- Experience with Spark data processing and ETL pipeline development.
- Knowledge of Git, CI/CD, and automation tools such as GitHub Actions, SonarQube, or Fortify.
- Experience developing REST APIs and testing with Pytest.
- Experience deploying, monitoring, and maintaining production applications.
- Ability to work independently, solve problems, and collaborate with multidisciplinary teams.
- Desirable: experience with AWS or Azure, Terraform, and infrastructure as code.
- Desirable: experience with MLOps tools such as MLflow and Kubeflow, and platforms such as Databricks or Cloudera.
- Desirable: experience with Airflow or Control-M orchestration.
- Desirable: knowledge of Kafka, Kibana, Dynatrace, and SQL or NoSQL databases.
- Desirable: experience with generative AI, LLMOps, RAG, LangChain, LangGraph, CrewAI, or MCP.
- Desirable: knowledge of NLP, OCR, and machine learning models.
- Desirable: professional English proficiency.
Responsibilities
- Develop and deploy AI and machine learning applications and models using Python.
- Manage container environments and deployments on Kubernetes.
- Design ETL processes using Python and Spark.
- Develop and integrate APIs for AI solutions.
- Implement and optimize CI/CD pipelines, automating testing and deployments.
- Monitor production applications to ensure performance and stability.
- Collaborate with data scientists, product owners, and technical teams to evolve solutions.
Skills
AirflowAWSAzureDatabricksDynatraceGitGitHubGitHub ActionsKafkaKibanaKubernetesPythonRESTSonarQubeSparkTerraformElasticsearch
Languages
English
Work schedule
Flexible working arrangements
Industry
Technology consultingArtificial intelligence
Relocation
No