Weareseekingahighlyskilled Data Engineer / Machine Learning Engineerto join our Applied AI Team. The idóneo 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. Collaboratecloselywith Data Scientiststotranslatenotebooks andprototypesintorobust,production-ready MLsystems. Buildandmaintainfeaturepipelines and dataabstractionsthatenablereproducible andreliablemodelbehavior. Ensuredataquality,versioning, andtraceabilityacrossdatasetsandmodels. Optimizepipelines and MLworkloadsforperformance,scalability, andcostefficiency.



Workwith Dev Ops and Platformteamstodeploysolutionsusingcontainerizationand CI/CDbestpractices. Contributetodefiningdataengineeringand MLOpsstandardsacross AI Labs. Participateincodereviews,documentation, andmentoringtofostera cultureofengineeringexcellence. Requirements and personal skills Proficientin Spanish and English,writtenand verbalcommunication. Strongproficiencyin Python,includingcleancodepractices,packaging, and modulardesign. Solidunderstandingofsoftwareengineeringprinciples(OOP, SOLID,testing,versioncontrol). Hands-onexperiencebuildingdata pipelines(ETL / ELT)using Python-basedframeworksorcustomsolutions. Experienceworkingwithmachinelearningworkflows,includingmodeltraining,evaluation, anddeployment. Familiaritywith RESTAPIsandservice-basedarchitectures(Fast API, Flask,orsimilar). Strongexperiencewith Gitandcollaborativedevelopmentworkflows. Experiencewithcontainerization(Docker)andcloudenvironments(AWSor Azure). Experiencewith MLOpspractices(modelversioning,monitoring,driftdetection,retrainingstrategies). Familiaritywithorchestrationtools(e.G., Airflow, Prefect, Dagster). Experiencewithdatastoragesystems(SQL / No SQLdatabases, datalakes,objectstorage). Experiencedeployingoroperating MLsystemsinregulatedorhigh-reliabilityenvironments. Familiaritywith MLframeworksandscientificlibraries(Num Py, Pandas, Scikit-learn, Py Torch, Tensor Flow). Interestinapplied AItopicssuchas NLP, LLM-basedsystems,orscientificcomputing. #J-18808-Ljbffr

📌 Data Engineer (Madrid)
🏢 Insud Pharma
📍 Madrid