AI research engineer
XxxxxxxisanEuropeandeep-techstartupbuildinganewinfrastructurelayerfor AI-powered softwaresystems.
Our corebeliefissimple,AI doesnotprimarilysufferfromalackof models,itsuffersfroma lackof reliable,structuredandgovernedcontext.
Today’sLLMsoperateon limited,staticcontextwindows,oftendisconnectedfromreal-world softwaresystems.Thisresultsinhallucinations,brittleautomation,technicaldebtamplification andpreventstrueAI autonomy.
Wearebuildingacontextintelligenceplatformfor codeandsoftwaresystems,designedto aggregate,structureandexposestatic,historicalanddynamiccontext,comingfromsourcecode, architectures,businesslogic,runtimebehavior,logs,incidents,supportticketsandoperational signals.
Thiscontextbecomesinfrastructure,consumableby humansandby AI systems. Our technicalplayground
AtXxxxxxx,AI isnotaproductfeature. Itisthecoresystem.
Our work spansacrosshigh-impact,research-gradetopics,including:
- Advanced semantic representations of source code and large-scale software systems
- Alignment between human intent, actual source code and runtime behavior
- Agent orchestration powered by governed, high-fidelity context
- Scaling AI systems in mission-critical enterprise environments
- Xxxxxxx is an agnostic to any AI Models service provider and any vector database provider
Weoperateattheintersectionof AI research,softwareengineering,systemsdesignandreal- worldproductionconstraints.
KeyResponsibilities
Webelievethatthebestresearchisdrivenby strongengineeringfoundations.As partof theAI researchteam,you willoperateacrossthefulllifecycleof advancedmachinelearningsystems, fromideationtoproductiondeployment,withastrongemphasison robustness,precisionand real-worldimpact.Your responsibilitiesinclude:
Researchandmodeling
- Design,trainanditerateon neuralrepresentationsoptimizedfor similaritysearch, includingdense,hybridandmulti-vectorapproaches
- Researchandimplementsemanticvectorizationtechniquesfor high-value,high-signal content,includingstructureddata,unstructureddataandcode-relatedartifacts
- Explorenovelembeddingstrategiesthatcapturesemanticintent,structureandbehavior, notjustsurface-levelsimilarity
- Investigatetrade-offsbetweenembeddingdimensionality,expressiveness,latencyand cost
- Continuouslyimproveprecisionandrecallinlarge-scalevectorsearchsystems
- Developevaluationprotocolsandbenchmarksfor similarity,relevanceandcontextual accuracy
Contextualizationof dataintocode-centricrepresentations
- Improvecontentpolarization,aligninggenericdatatowardprecisesoftwareconstructs suchasmodules,functions,services,domainsor businesscomponents
- Designrepresentationsthatenablecontext-awarereasoningfor AI agentsoperatingon Codebases
- Ensurestrongalignmentbetweensemanticembeddings,codestructureandruntime behavior
- Buildresearchcodethatsupportsfastiteration,reproducibilityandcollaborative experimentation
- Own modelperformanceend-to-end,evaluationquality,trainingefficiency,inference latencyandscalability
- Partnercloselywithproductandplatformteamstodeployresearchoutputsinto productionsystems
- Contributetointernaltools,frameworksandbestpracticesthataccelerateresearch velocity
- Shareinsights,experimentsandfailuresclearlywiththeteam
- Staycurrentwiththestateoftheartinrepresentationlearning,retrievalsystemsand appliedAI research
AtXxxxxxx,researchisnotisolatedfromreality.Youareexpectedtothinkdeeply,experiment boldlyandshipresponsibly,withyourworkdirectlyshapinghow AI systemsunderstand, navigateandreasonovercomplexsoftwaresystemsatscale.
RequiredQualifications
- Strongfundamentalsof softwareengineering
- Strongknowledgeof Python,anditsMLframeworks
- Experiencewith:
- Fulllifecycleof AI modeldevelopment
- DevelopingnewMLmethods,algorithmsandmodels