Senior Machine Learning Engineer - Data Science & AnalyticsContract Length: 6-18 MonthsLocation: Remote (U.S. preferred); Chicago candidates strongly preferredCore ResponsibilitiesDesign and implement scalable backend architectures supporting machine learning productsBuild and operationalize AI/ML services across the full product lifecycle: Data ingestionFeature engineeringModel integrationReal-time inferenceBatch processingDeployment and monitoringPartner closely with Data Scientists to productionize machine learning modelsDevelop streaming and batch data processing workflows at scaleImplement infrastructure-as-code and CI/CD deployment pipelinesEnhance and maintain feature store workflows and ML data pipelinesOptimize latency, scalability, and reliability of ML systemsBuild services supporting personalization, recommendation engines, search, analytics, and conversational AI experiencesCollaborate with Data Engineering, Architecture, Governance, and Security teamsSupport cloud-native ML infrastructure within AWS and Google Cloud environmentsContribute to system design discussions and technical architecture decisionsRequired Technical QualificationsMust-Have Skills 5+ years of software engineering experience implementing cloud-native product solutionsStrong experience building backend systems supporting ML/algorithmic productsExpertise with: PythonSQLPySparkDockerStrong AWS cloud experienceExperience with Google Cloud Platform (GCP) Experience building streaming and batch data architectures at scaleStrong system design and backend architecture experienceExperience operating in Agile environmentsExperience with DevOps and CI/CD practicesAbility to handle ambiguity and rapidly changing requirementsStrong communication and collaboration skillsPreferred / Nice-to-Have SkillsExperience with SageMakerUnderstanding of feature storesHospitality or personalization/recommendation system experienceReal-time ML inference and personalization systemsInfrastructure-as-code implementation experienceExperience supporting AI/LLM-enabled applicationsTeam uses existing LLMs rather than building foundational modelsMaster's degree in Computer Science, Software Engineering, or related fieldBachelor's degree + strong equivalent experience acceptableTechnical EnvironmentCore TechnologiesPythonSQLPySparkDockerAWSGCPML/AI Focus AreasReal-time personalizationRecommendation systemsSearch platformsInternal analytics toolingChat interfaces and AI-assisted workflows
