WeareseekingahighlyskilledData Engineer / Machine Learning Engineerto join our Applied AI Team. The adecuado candidate combines strong software engineering foundations with hands-on experience in data pipelines and machine learning systems, and enjoys working at the intersection between data, models, and production systems.

As a Data Engineer / MLE at AI Labs, you will work closely with data scientists, software engineers, and product owners todesign, build, deploy, and operate end-to-end data and machine learning solutionsacross multiple business units — including Regulatory, Clinical Trials, R&D;, Pharmacovigilance, and Drug Manufacturing.

This role is critical to ensuring that AI models move reliably from experimentation to production, supported by scalable data pipelines, robust ML infrastructure, and strong engineering standards.

Specific Responsibilities

Design,build, andmaintainscalabledata pipelinesfordataingestion,transformation, andserving,supportingbothanalyticsand machinelearninguse cases.

Developandproductionizemachinelearningpipelines,coveringtraining,validation,deployment, andmonitoring.

CollaboratecloselywithDataScientiststotranslatenotebooks andprototypesintorobust,production-readyMLsystems.

Buildandmaintainfeaturepipelines and dataabstractionsthatenablereproducible andreliablemodelbehavior.

Ensuredataquality,versioning, andtraceabilityacrossdatasetsandmodels.

Optimizepipelines and MLworkloadsforperformance,scalability, andcostefficiency.





WorkwithDevOps andPlatformteamstodeploysolutionsusingcontainerizationand CI/CDbestpractices.

ContributetodefiningdataengineeringandMLOpsstandardsacrossAI Labs.Participateincodereviews,documentation, andmentoringtofostera cultureofengineeringexcellence.

Requirements and personal skills

ProficientinSpanish and English,writtenand verbalcommunication.

StrongproficiencyinPython,includingcleancodepractices,packaging, and modulardesign.

Solidunderstandingofsoftwareengineeringprinciples(OOP, SOLID,testing,versioncontrol).

Hands-onexperiencebuildingdata pipelines(ETL / ELT)usingPython-basedframeworksorcustomsolutions.

Experienceworkingwithmachinelearningworkflows,includingmodeltraining,evaluation, anddeployment.

FamiliaritywithRESTAPIsandservice-basedarchitectures(FastAPI, Flask,orsimilar).

StrongexperiencewithGitandcollaborativedevelopmentworkflows.

Experiencewithcontainerization(Docker)andcloudenvironments(AWSorAzure).

ExperiencewithMLOpspractices(modelversioning,monitoring,driftdetection,retrainingstrategies).

Familiaritywithorchestrationtools(e.g.,Airflow,Prefect,Dagster).

Experiencewithdatastoragesystems(SQL / NoSQLdatabases, datalakes,objectstorage).

ExperiencedeployingoroperatingMLsystemsinregulatedorhigh-reliabilityenvironments.

FamiliaritywithMLframeworksandscientificlibraries(NumPy, Pandas,Scikit-learn,PyTorch,TensorFlow).

InterestinappliedAItopicssuchas NLP, LLM-basedsystems,orscientificcomputing.

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📌 Data engineer (Comunidad de Madrid)
🏢 Insud Pharma
📍 Comunidad de Madrid