Jobs at Zaimler

The Cloud Infrastructure Engineer will design and build cloud infrastructure for zaimler's platform, focusing on scalability, security, and optimizations for ML/AI workloads.

The role involves developing scalable ML algorithms, optimizing LLM inference performance, managing model serving pipelines, and collaborating with data engineers for efficient knowledge graph generation.

This role involves bridging research and applied engineering, overseeing training infrastructure, optimizing workflows, and setting technical strategies for AI/ML deployment at zaimler.

As the Founding Cloud Infrastructure Engineer, you'll design secure cloud infrastructures using AWS/Azure/GCP, support distributed AI workloads, manage GPU resources, and collaborate on ML initiatives.

Own the product end to end, define the core product surfaces, drive adoption, and collaborate with cross-functional teams and customers to validate solutions and prioritize tasks.

The Director of Marketing will define messaging, lead product launches, create sales assets, gather customer insights, and collaborate across functions to establish zaimler's market presence in B2B enterprise.

The Backend Engineer will design, implement, and scale microservices for AI and data platforms, defining service boundaries and APIs while contributing to deployment infrastructure.

Embed automated security testing into CI/CD, secure cloud and IaC, automate vulnerability scanning and remediation, support incident response and compliance (SOC 2/GDPR), and partner with DevOps to reduce risk and shift security left.

Build integrations exposing zaimler's query engine to Power BI and Microsoft Fabric, enabling metrics, dashboards, graph queries (e.g., Cypher), and natural-language queries for non-technical users; collaborate with customers and the query-engine team to define primitives and troubleshoot integrations.

Design and build scalable, fault-tolerant query engines and integrations with modern data lake formats; optimize query execution using vectorized processing, cost-based optimization, and caching; extend or contribute to open-source platforms; collaborate with product, data science, and engineering teams to align solutions with business needs.

Own technical engagement for enterprise deals in EMEA: run demos and discovery, scope and drive proofs of value to production, translate customer environments into actionable product feedback, build the pre-sales playbook, and partner with ML and infra engineers on deployments. Regular on-site travel and customer-facing technical credibility required.

Build and own end-to-end product surfaces: React/TypeScript frontends, APIs, and backend services in Python/Go. Ship features, work with customers, design APIs/data models, operate cloud deployments, and iterate on production systems to make AI infrastructure legible and fast.