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AI Data Engineer
AI Data Engineer at GE HealthCare's Advanced Imaging Solutions builds shared data tools, ingestion/annotation pipelines, and AI infrastructure for global ultrasound teams — evaluating platforms, running benchmarks, and operating shared environments in Python/SQL on cloud. Based in Zipf, Austria, hybrid with min. 3 office days/week.
Senior Full Stack Developer
Senior full-stack engineer at a digital consultancy serving public and private sector clients: designs and builds scalable services and REST APIs in Kotlin/Java (Spring Boot), owns deployment pipelines on cloud and Kubernetes (AWS/Azure/GCP, Docker, Terraform), and mentors other engineers. Hybrid role, 2 days onsite in Bristol.
Forward-Deployed Engineer (f/m/d)
Forward-Deployed Engineer at Zeit AI (YC S24) works hands-on with customers to connect their data (ERP exports, CRM, spreadsheets, internal databases) to ZeitMind, an autonomous AI data engineer. Day to day you model business logic, deploy production data applications, and feed learnings back into the product; core skills are SQL and working with large datasets.
Software Engineer, Spark Platform
Builds and operates DoorDash's in-house Apache Spark platform — runtime upgrades, multi-tenant scheduling and executor bin-packing on Kubernetes, cluster lifecycle automation, and observability/incident automation — serving company-wide data, analytics, and ML workloads. Core stack: Spark, Kubernetes, AWS, and Python/Go/Scala/Java.
Senior Software Engineer, Spark Platform
Senior engineer setting multi-year technical direction for DoorDash's in-house Apache Spark platform on Kubernetes — owning the runtime, remote shuffle service, scheduler, and reliability tooling that run data, analytics, and ML workloads at scale. Core tech: Spark, Kubernetes, distributed systems, Scala/Java/Python/Go.
Software Engineer, Data Platform
Software engineer on DoorDash's Core Data Platform team, building and scaling the frameworks behind its analytical data stack — ingestion, streaming/batch compute, tooling, and data governance — using Spark, Flink, Kafka, Airflow, and lakehouse tech. Requires 2+ years' experience and being based in or relocating to the Bay Area, Seattle, or New York.