{"schemaVersion":"jobsearcher.job.v1","id":"dcc2c43091bcf3def5a9f848","url":"https://jobsearcher.com/jobs/dcc2c43091bcf3def5a9f848","canonicalUrl":"https://jobsearcher.com/jobs/dcc2c43091bcf3def5a9f848","title":"Data Engineer (Machine Learning / Infrastructure)","description":"Data Engineer (Machine Learning / Infrastructure)National Security / Geospatial IntelligenceAustin, TC (or Kansas or Oklahoma)$150,000 - $165,000 The CompanyA highly specialized R&D firm backed by multi-year, mission-critical federal funding.They build next-generation sensor fusion platforms to process complex, real-time physical telemetry.They operate a high-autonomy, low-bureaucracy engineering culture focused entirely on technical problem-solving.Why Join?Pure building: Contribute to modern open-source ecosystems without the pressure of designing enterprise architectures from absolute scratch.Bridge the gap: Partner directly with data scientists to turn prototype algorithms into production-ready distributed systems.Complex data: Tackle massive scaling challenges using continuous spatiotemporal, numerical, and sensor data.Pivot your career: Transition from standard data engineering into highly specialized Machine Learning infrastructure.The RoleA technical, hands-on role where you will:Build and optimize automated pipelines for the ML lifecycle (compiling training datasets, managing model versioning).Deploy and scale containerized Python microservices within an existing Kubernetes cluster.Ingest and process massive streams of time-series and spatiotemporal telemetry from remote sensors.Translate applied research requirements into scalable, reliable platform engineering solutions.Troubleshoot distributed environments for high-throughput physical data (strictly avoiding LLM or GenAI ecosystems).The Essential RequirementsEligible to obtain a U.S. Security Clearance (U.S. Citizenship required).3+ years in Data/Platform Engineering or ML Infrastructure with a strong foundation in Python.Hands-on experience deploying and managing workloads in Kubernetes.ML Lifecycles: Proven understanding of model deployment, versioning, and training dataset construction.Domain Data: Direct experience processing physical sensor, time-series, or spatiotemporal data (e.g., IoT, telemetry).What Will Make You Stand OutA career path transitioning from Data Science into Platform Engineering.Professional background in the Defense, Telecom, Space, or Industrial IoT sectors.Familiarity with event-driven architectures and open-source data orchestration tools.If you are interested in this role, please apply with your resume through this site.DisclaimerNo terminology in this advert is intended to discriminate on the grounds of age, sex, race, religion or belief, disability, pregnancy and maternity, marriage and civil partnership, sexual orientation, gender, and/or gender reassignment, and we confirm that we are happy to accept applications from anyone for this role. Attis Global Ltd operates as an employment agency and employment business. More information can be found at attisglobal.com.Keywords for Search (SEO)Data Platform Engineer, Machine Learning Operations, Data Engineer, Python Developer, Kubernetes Administrator, ML Infrastructure Builder, Time-Series Data Specialist, Sensor Telemetry Architect, Spatiotemporal Tech, Defense Technology, MLOps, IoT Data Pipelines","company":"Attis","rawCompany":"attis","city":"Austin","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-04-12T19:22:36.482Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer (Machine Learning / Infrastructure)","description":"Data Engineer (Machine Learning / Infrastructure)National Security / Geospatial IntelligenceAustin, TC (or Kansas or Oklahoma)$150,000 - $165,000 The CompanyA highly specialized R&D firm backed by multi-year, mission-critical federal funding.They build next-generation sensor fusion platforms to process complex, real-time physical telemetry.They operate a high-autonomy, low-bureaucracy engineering culture focused entirely on technical problem-solving.Why Join?Pure building: Contribute to modern open-source ecosystems without the pressure of designing enterprise architectures from absolute scratch.Bridge the gap: Partner directly with data scientists to turn prototype algorithms into production-ready distributed systems.Complex data: Tackle massive scaling challenges using continuous spatiotemporal, numerical, and sensor data.Pivot your career: Transition from standard data engineering into highly specialized Machine Learning infrastructure.The RoleA technical, hands-on role where you will:Build and optimize automated pipelines for the ML lifecycle (compiling training datasets, managing model versioning).Deploy and scale containerized Python microservices within an existing Kubernetes cluster.Ingest and process massive streams of time-series and spatiotemporal telemetry from remote sensors.Translate applied research requirements into scalable, reliable platform engineering solutions.Troubleshoot distributed environments for high-throughput physical data (strictly avoiding LLM or GenAI ecosystems).The Essential RequirementsEligible to obtain a U.S. Security Clearance (U.S. Citizenship required).3+ years in Data/Platform Engineering or ML Infrastructure with a strong foundation in Python.Hands-on experience deploying and managing workloads in Kubernetes.ML Lifecycles: Proven understanding of model deployment, versioning, and training dataset construction.Domain Data: Direct experience processing physical sensor, time-series, or spatiotemporal data (e.g., IoT, telemetry).What Will Make You Stand OutA career path transitioning from Data Science into Platform Engineering.Professional background in the Defense, Telecom, Space, or Industrial IoT sectors.Familiarity with event-driven architectures and open-source data orchestration tools.If you are interested in this role, please apply with your resume through this site.DisclaimerNo terminology in this advert is intended to discriminate on the grounds of age, sex, race, religion or belief, disability, pregnancy and maternity, marriage and civil partnership, sexual orientation, gender, and/or gender reassignment, and we confirm that we are happy to accept applications from anyone for this role. Attis Global Ltd operates as an employment agency and employment business. More information can be found at attisglobal.com.Keywords for Search (SEO)Data Platform Engineer, Machine Learning Operations, Data Engineer, Python Developer, Kubernetes Administrator, ML Infrastructure Builder, Time-Series Data Specialist, Sensor Telemetry Architect, Spatiotemporal Tech, Defense Technology, MLOps, IoT Data Pipelines","datePosted":"2026-04-12T19:22:36.482Z","dateModified":"2026-04-12T19:22:36.482Z","hiringOrganization":{"@type":"Organization","name":"Attis","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Austin","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"dcc2c43091bcf3def5a9f848"},"url":"https://jobsearcher.com/jobs/dcc2c43091bcf3def5a9f848"}}